no code implementations • ECCV 2020 • Frank Verbiest, Marc Proesmans, Luc van Gool
Instead of using a generalized camera approach, we propose a novel approach to jointly optimize a traditional camera model, and a mathematical representation of the windshield’s surface.
1 code implementation • ECCV 2020 • Guolei Sun, Salman Khan, Wen Li, Hisham Cholakkal, Fahad Shahbaz Khan, Luc van Gool
This way, in an effort to fix localization errors, our loss provides an extra supervisory signal that helps the model to better discriminate between similar classes.
no code implementations • 30 May 2024 • Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan, Mengyuan Liu, Rita Cucchiara, Luc van Gool, Ming-Hsuan Yang, Nicu Sebe
Additionally, for IR, it is commonly noted that small segments of a degraded image, particularly those closely aligned semantically, provide particularly relevant information to aid in the restoration process, as they contribute essential contextual cues crucial for accurate reconstruction.
no code implementations • 28 May 2024 • Yuedong Tan, Zongwei Wu, Yuqian Fu, Zhuyun Zhou, Guolei Sun, Chao Ma, Danda Pani Paudel, Luc van Gool, Radu Timofte
With the emergence of a single large model capable of successfully solving a multitude of tasks in NLP, there has been growing research interest in achieving similar goals in computer vision.
1 code implementation • 26 May 2024 • Erik Sandström, Keisuke Tateno, Michael Oechsle, Michael Niemeyer, Luc van Gool, Martin R. Oswald, Federico Tombari
In response, we propose the first RGB-only SLAM system with a dense 3D Gaussian map representation that utilizes all benefits of globally optimized tracking by adapting dynamically to keyframe pose and depth updates by actively deforming the 3D Gaussian map.
no code implementations • 7 May 2024 • David Borts, Erich Liang, Tim Brödermann, Andrea Ramazzina, Stefanie Walz, Edoardo Palladin, Jipeng Sun, David Bruggemann, Christos Sakaridis, Luc van Gool, Mario Bijelic, Felix Heide
Neural fields have been broadly investigated as scene representations for the reproduction and novel generation of diverse outdoor scenes, including those autonomous vehicles and robots must handle.
no code implementations • 8 Apr 2024 • Zhipeng Zhang, Zhimin Wei, Guolei Sun, Peng Wang, Luc van Gool
In the field of visual affordance learning, previous methods mainly used abundant images or videos that delineate human behavior patterns to identify action possibility regions for object manipulation, with a variety of applications in robotic tasks.
no code implementations • 8 Apr 2024 • Saman Motamed, Wouter Van Gansbeke, Luc van Gool
With recent advances in image and video diffusion models for content creation, a plethora of techniques have been proposed for customizing their generated content.
no code implementations • 6 Apr 2024 • Juan Wen, Yawei Li, Chao Zhang, Weiyan Hou, Radu Timofte, Luc van Gool
Integration of attention mechanisms across feature and positional dimensions further enhances the recovery of fine details.
2 code implementations • 4 Apr 2024 • Wencan Cheng, Hao Tang, Luc van Gool, Jong Hwan Ko
Extracting keypoint locations from input hand frames, known as 3D hand pose estimation, is a critical task in various human-computer interaction applications.
1 code implementation • 4 Apr 2024 • Rui Li, Tobias Fischer, Mattia Segu, Marc Pollefeys, Luc van Gool, Federico Tombari
We propose KYN, a novel method for single-view scene reconstruction that reasons about semantic and spatial context to predict each point's density.
no code implementations • 4 Apr 2024 • Elham Amin Mansour, Ozan Unal, Suman Saha, Benjamin Bejar, Luc van Gool
A key challenge in panoptic UDA is reducing the domain gap between a labeled source and an unlabeled target domain while harmonizing the subtasks of semantic and instance segmentation to limit catastrophic interference.
no code implementations • 3 Apr 2024 • Ata Çelen, Guo Han, Konrad Schindler, Luc van Gool, Iro Armeni, Anton Obukhov, Xi Wang
Interior design allows us to be who we are and live how we want - each design is as unique as our distinct personality.
no code implementations • 1 Apr 2024 • Reni Paskaleva, Mykyta Holubakha, Andela Ilic, Saman Motamed, Luc van Gool, Danda Paudel
However, emotions are often compound, e. g. happily surprised, and can be mapped to the action units (AUs) used for expressing emotions, and trivially to the canonical ones.
1 code implementation • 28 Mar 2024 • Ganlin Zhang, Erik Sandström, Youmin Zhang, Manthan Patel, Luc van Gool, Martin R. Oswald
To alleviate this issue, with the aid of a monocular depth estimator, we introduce a novel DSPO layer for bundle adjustment which optimizes the pose and depth of keyframes along with the scale of the monocular depth.
1 code implementation • 27 Mar 2024 • Luigi Piccinelli, Yung-Hsu Yang, Christos Sakaridis, Mattia Segu, Siyuan Li, Luc van Gool, Fisher Yu
However, the remarkable accuracy of recent MMDE methods is confined to their training domains.
Ranked #4 on Monocular Depth Estimation on NYU-Depth V2 (using extra training data)
no code implementations • 24 Mar 2024 • Guillaume Thiry, Hao Tang, Radu Timofte, Luc van Gool
Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers.
no code implementations • 11 Mar 2024 • Muhammad Saif Ullah Khan, Muhammad Ferjad Naeem, Federico Tombari, Luc van Gool, Didier Stricker, Muhammad Zeshan Afzal
We propose FocusCLIP, integrating subject-level guidance--a specialized mechanism for target-specific supervision--into the CLIP framework for improved zero-shot transfer on human-centric tasks.
Ranked #1 on Age Classification on EMOTIC
1 code implementation • 1 Mar 2024 • Zhaochong An, Guolei Sun, Yun Liu, Fayao Liu, Zongwei Wu, Dan Wang, Luc van Gool, Serge Belongie
The former arises from non-uniform point sampling, allowing models to distinguish the density disparities between foreground and background for easier segmentation.
Few-shot 3D Point Cloud Semantic Segmentation Segmentation +1
no code implementations • 14 Feb 2024 • Lorenzo Liso, Erik Sandström, Vladimir Yugay, Luc van Gool, Martin R. Oswald
Neural RGBD SLAM techniques have shown promise in dense Simultaneous Localization And Mapping (SLAM), yet face challenges such as error accumulation during camera tracking resulting in distorted maps.
no code implementations • 5 Feb 2024 • Yuqian Fu, Yu Wang, Yixuan Pan, Lian Huai, Xingyu Qiu, Zeyu Shangguan, Tong Liu, Yanwei Fu, Luc van Gool, Xingqun Jiang
This paper studies the challenging cross-domain few-shot object detection (CD-FSOD), aiming to develop an accurate object detector for novel domains with minimal labeled examples.
no code implementations • 4 Feb 2024 • Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan, Mengyuan Liu, Rita Cucchiara, Luc van Gool, Nicu Sebe
While it is crucial to capture global information for effective image restoration (IR), integrating such cues into transformer-based methods becomes computationally expensive, especially with high input resolution.
no code implementations • 3 Feb 2024 • Zixiang Zhao, Lilun Deng, Haowen Bai, Yukun Cui, Zhipeng Zhang, Yulun Zhang, Haotong Qin, Dongdong Chen, Jiangshe Zhang, Peng Wang, Luc van Gool
Therefore, we introduce a novel fusion paradigm named image Fusion via vIsion-Language Model (FILM), for the first time, utilizing explicit textual information in different source images to guide image fusion.
1 code implementation • 27 Jan 2024 • Diandian Guo, Deng-Ping Fan, Tongyu Lu, Christos Sakaridis, Luc van Gool
The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation (VSS) for driving scenes.
no code implementations • 23 Jan 2024 • Tim Brödermann, David Bruggemann, Christos Sakaridis, Kevin Ta, Odysseas Liagouris, Jason Corkill, Luc van Gool
Achieving level-5 driving automation in autonomous vehicles necessitates a robust semantic visual perception system capable of parsing data from different sensors across diverse conditions.
no code implementations • 15 Jan 2024 • Hao Tang, Ling Shao, Nicu Sebe, Luc van Gool
Finally, we propose a novel self-guided pre-training method for graph representation learning.
Generative Adversarial Network Graph Representation Learning +1
no code implementations • 10 Jan 2024 • Mohamad Shahbazi, Liesbeth Claessens, Michael Niemeyer, Edo Collins, Alessio Tonioni, Luc van Gool, Federico Tombari
We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes.
1 code implementation • 4 Jan 2024 • Muhammad Uzair Khattak, Muhammad Ferjad Naeem, Muzammal Naseer, Luc van Gool, Federico Tombari
While effective, most of these works require labeled data which is not practical, and often struggle to generalize towards new datasets due to over-fitting on the source data.
no code implementations • 24 Dec 2023 • Rashik Shrestha, Ajad Chhatkuli, Menelaos Kanakis, Luc van Gool
Such an approach of optimization allows us to discard learning knowledge already present in non-differentiable functions such as the hand-crafted descriptors and only learn the residual knowledge in the main network branch.
no code implementations • 20 Dec 2023 • Junru Lin, Asen Nachkov, Songyou Peng, Luc van Gool, Danda Pani Paudel
To foster this line of research, we also propose a simple yet novel visual odometry scheme that uses a hybrid combination of volumetric and warping-based image renderings.
no code implementations • 18 Dec 2023 • Asen Nachkov, Martin Danelljan, Danda Pani Paudel, Luc van Gool
For the enhanced safety of AVs, modeling perception uncertainty in BEV is crucial.
no code implementations • 13 Dec 2023 • M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel, Nikola Popovic, Christian Vater, Otmar Hilliges, Luc van Gool, Xi Wang
In contrast, we focus on inferring the ego trajectory of a driver's vehicle using their gaze data.
no code implementations • 5 Dec 2023 • Weijie Wang, Guofeng Mei, Bin Ren, Xiaoshui Huang, Fabio Poiesi, Luc van Gool, Nicu Sebe, Bruno Lepri
The cornerstone of ZeroReg is the novel transfer of image features from keypoints to the point cloud, enriched by aggregating information from 3D geometric neighborhoods.
no code implementations • 5 Dec 2023 • Yuru Jia, Lukas Hoyer, Shengyu Huang, Tianfu Wang, Luc van Gool, Konrad Schindler, Anton Obukhov
Large, pretrained latent diffusion models (LDMs) have demonstrated an extraordinary ability to generate creative content, specialize to user data through few-shot fine-tuning, and condition their output on other modalities, such as semantic maps.
no code implementations • 29 Nov 2023 • Sanghwan Kim, Daoji Huang, Yongqin Xian, Otmar Hilliges, Luc van Gool, Xi Wang
Understanding human activity is a crucial yet intricate task in egocentric vision, a field that focuses on capturing visual perspectives from the camera wearer's viewpoint.
1 code implementation • 28 Nov 2023 • Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this paper, we showcase the effectiveness of optimizing monocular camera poses as a continuous function of time.
1 code implementation • 27 Nov 2023 • Zongwei Wu, Jilai Zheng, Xiangxuan Ren, Florin-Alexandru Vasluianu, Chao Ma, Danda Pani Paudel, Luc van Gool, Radu Timofte
In practice, most existing RGB trackers learn a single set of parameters to use them across datasets and applications.
Ranked #17 on Rgb-T Tracking on LasHeR
1 code implementation • 27 Nov 2023 • Lukas Hoyer, David Joseph Tan, Muhammad Ferjad Naeem, Luc van Gool, Federico Tombari
In SemiVL, we propose to integrate rich priors from VLM pre-training into semi-supervised semantic segmentation to learn better semantic decision boundaries.
Ranked #1 on Semi-Supervised Semantic Segmentation on PASCAL VOC 2012 732 labeled (using extra training data)
no code implementations • 27 Nov 2023 • Ozan Unal, Dengxin Dai, Lukas Hoyer, Yigit Baran Can, Luc van Gool
As 3D perception problems grow in popularity and the need for large-scale labeled datasets for LiDAR semantic segmentation increase, new methods arise that aim to reduce the necessity for dense annotations by employing weakly-supervised training.
Ranked #1 on 3D Semantic Segmentation on ScribbleKITTI
no code implementations • 23 Nov 2023 • Saman Motamed, Danda Pani Paudel, Luc van Gool
To enable customized content creation based on a few example images of a concept, methods such as Textual Inversion and DreamBooth invert the desired concept and enable synthesizing it in new scenes.
no code implementations • 21 Nov 2023 • Janis Postels, Yannick Strümpler, Klara Reichard, Luc van Gool, Federico Tombari
Neural Fields (NFs) have gained momentum as a tool for compressing various data modalities - e. g. images and videos.
1 code implementation • 20 Nov 2023 • JieZhang Cao, Yue Shi, Kai Zhang, Yulun Zhang, Radu Timofte, Luc van Gool
Due to the inherent property of diffusion models, most existing methods need long serial sampling chains to restore HQ images step-by-step, resulting in expensive sampling time and high computation costs.
1 code implementation • 20 Nov 2023 • Nikola Popovic, Dimitrios Christodoulou, Danda Pani Paudel, Xi Wang, Luc van Gool
In this work, we propose to predict 3D eye gaze from weak supervision of eye semantic segmentation masks and direct supervision of a few 3D gaze vectors.
no code implementations • 19 Nov 2023 • Jingyun Liang, Yuchen Fan, Kai Zhang, Radu Timofte, Luc van Gool, Rakesh Ranjan
While recent years have witnessed great progress on using diffusion models for video generation, most of them are simple extensions of image generation frameworks, which fail to explicitly consider one of the key differences between videos and images, i. e., motion.
no code implementations • 14 Nov 2023 • Pierre-François De Plaen, Nicola Marinello, Marc Proesmans, Tinne Tuytelaars, Luc van Gool
The DEtection TRansformer (DETR) opened new possibilities for object detection by modeling it as a translation task: converting image features into object-level representations.
Ranked #1 on Multiple Object Tracking on BDD100K test
no code implementations • 8 Nov 2023 • Nishant Jain, Suryansh Kumar, Luc van Gool
The key ideas presented in this paper are (i) Recovering accurate camera parameters via a robust pipeline from unposed day-to-day images is equally crucial in neural novel view synthesis problem; (ii) It is rather more practical to model object's content at different resolutions since dramatic camera motion is highly likely in day-to-day unposed images.
no code implementations • 6 Nov 2023 • Zador Pataki, Mohammad Altillawi, Menelaos Kanakis, Rémi Pautrat, Fengyi Shen, Ziyuan Liu, Luc van Gool, Marc Pollefeys
Our proposed method enhances cross-domain localization performance, significantly reducing the performance gap.
no code implementations • 2 Nov 2023 • Qingsen Yan, Tao Hu, Yuan Sun, Hao Tang, Yu Zhu, Wei Dong, Luc van Gool, Yanning Zhang
To address this challenge, we formulate the HDR deghosting problem as an image generation that leverages LDR features as the diffusion model's condition, consisting of the feature condition generator and the noise predictor.
no code implementations • 20 Oct 2023 • Muhammad Ferjad Naeem, Yongqin Xian, Xiaohua Zhai, Lukas Hoyer, Luc van Gool, Federico Tombari
However, the contrastive objective used by these models only focuses on image-text alignment and does not incentivise image feature learning for dense prediction tasks.
1 code implementation • NeurIPS 2023 • Zhejun Zhang, Alexander Liniger, Christos Sakaridis, Fisher Yu, Luc van Gool
The real-world deployment of an autonomous driving system requires its components to run on-board and in real-time, including the motion prediction module that predicts the future trajectories of surrounding traffic participants.
no code implementations • 18 Oct 2023 • Jan-Nico Zaech, Martin Danelljan, Tolga Birdal, Luc van Gool
Adiabatic quantum computing (AQC) is a promising approach for discrete and often NP-hard optimization problems.
no code implementations • 23 Sep 2023 • Ozan Unal, Dengxin Dai, Ali Tamer Unal, Luc van Gool
Finally we propose a semi-supervised learning approach to utilize all frames within our dataset and improve performance.
2 code implementations • 15 Sep 2023 • Tianfu Wang, Menelaos Kanakis, Konrad Schindler, Luc van Gool, Anton Obukhov
Diffusion-based text-to-image models ignited immense attention from the vision community, artists, and content creators.
no code implementations • ICCV 2023 • Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this work, we develop a novel method to model the deformable neural radiance fields using RGB and event cameras.
1 code implementation • 14 Sep 2023 • Zhaochong An, Guolei Sun, Zongwei Wu, Hao Tang, Luc van Gool
Modern approaches have proved the huge potential of addressing semantic segmentation as a mask classification task which is widely used in instance-level segmentation.
no code implementations • 8 Sep 2023 • Ozan Unal, Christos Sakaridis, Suman Saha, Fisher Yu, Luc van Gool
A common formulation to tackle 3D visual grounding is grounding-by-detection, where localization is done via bounding boxes.
no code implementations • ICCV 2023 • Thomas E. Huang, Yifan Liu, Luc van Gool, Fisher Yu
VTD is a promising new direction for exploring the unification of perception tasks in autonomous driving.
1 code implementation • 31 Aug 2023 • Shuang Xu, Yifan Wang, Zixiang Zhao, Jiangjun Peng, Xiangyong Cao, Deyu Meng, Yulun Zhang, Radu Timofte, Luc van Gool
NGR is applicable to various image types and different image processing tasks, functioning in a zero-shot learning fashion, making it a versatile and plug-and-play regularizer.
1 code implementation • ICCV 2023 • Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc van Gool, Didier Stricker, Federico Tombari, Muhammad Zeshan Afzal
While the model faces a disjoint set of classes in each task in this setting, we argue that these classes can be encoded to the same embedding space of a pre-trained language encoder.
no code implementations • 26 Aug 2023 • Bin Xia, Yulun Zhang, Shiyin Wang, Yitong Wang, Xinglong Wu, Yapeng Tian, Wenming Yang, Radu Timotfe, Luc van Gool
Compared to traditional DMs, the compact IPR enables DiffI2I to obtain more accurate outcomes and employ a lighter denoising network and fewer iterations.
no code implementations • ICCV 2023 • Hanqing Wang, Wei Liang, Luc van Gool, Wenguan Wang
VLN-CE is a recently released embodied task, where AI agents need to navigate a freely traversable environment to reach a distant target location, given language instructions.
no code implementations • 8 Aug 2023 • Juan Wen, Shupeng Cheng, Peng Xu, BoWen Zhou, Radu Timofte, Weiyan Hou, Luc van Gool
Super Resolution (SR) and Camouflaged Object Detection (COD) are two hot topics in computer vision with various joint applications.
1 code implementation • 27 Jul 2023 • Haotong Qin, Ge-Peng Ji, Salman Khan, Deng-Ping Fan, Fahad Shahbaz Khan, Luc van Gool
Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI.
no code implementations • 25 Jul 2023 • Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool
Thus, online estimation of the lane graph is crucial for widespread and reliable autonomous navigation.
1 code implementation • 22 Jul 2023 • Hao Tang, Guolei Sun, Nicu Sebe, Luc van Gool
To tackle 2), we design an effective module to selectively highlight class-dependent feature maps according to the original semantic layout to preserve the semantic information.
no code implementations • ICCV 2023 • Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool
In this work, we propose an architecture and loss formulation to improve the accuracy of local lane graph estimates by using 3D object detection outputs.
1 code implementation • NeurIPS 2023 • Evangelos Ntavelis, Aliaksandr Siarohin, Kyle Olszewski, Chaoyang Wang, Luc van Gool, Sergey Tulyakov
We present a novel approach to the generation of static and articulated 3D assets that has a 3D autodecoder at its core.
no code implementations • 5 Jul 2023 • Rui Gong, Martin Danelljan, Han Sun, Julio Delgado Mangas, Luc van Gool
Intrigued by this result, we set out to explore how well diffusion-pretrained representations generalize to new domains, a crucial ability for any representation.
1 code implementation • CVPR 2023 • Henri De Plaen, Pierre-François De Plaen, Johan A. K. Suykens, Marc Proesmans, Tinne Tuytelaars, Luc van Gool
The approach is well suited for GPU implementation, which proves to be an advantage for large-scale models.
1 code implementation • 28 Jun 2023 • Daoji Huang, Otmar Hilliges, Luc van Gool, Xi Wang
We present Palm, a solution to the Long-Term Action Anticipation (LTA) task utilizing vision-language and large language models.
1 code implementation • 19 Jun 2023 • Erik Sandström, Kevin Ta, Luc van Gool, Martin R. Oswald
We present an uncertainty learning framework for dense neural simultaneous localization and mapping (SLAM).
no code implementations • 7 Jun 2023 • Han Sun, Rui Gong, Konrad Schindler, Luc van Gool
Domain adaptive object detection aims to leverage the knowledge learned from a labeled source domain to improve the performance on an unlabeled target domain.
1 code implementation • 27 May 2023 • Christos Sakaridis, David Bruggemann, Fisher Yu, Luc van Gool
Motivated by these findings, we propose to leverage stylization in performing feature-level adaptation by aligning the internal network features extracted by the encoder of the network from the original and the stylized view of each input image with a novel feature invariance loss.
3 code implementations • 19 May 2023 • Zixiang Zhao, Haowen Bai, Jiangshe Zhang, Yulun Zhang, Kai Zhang, Shuang Xu, Dongdong Chen, Radu Timofte, Luc van Gool
These components enable the net training to follow the principles of the natural sensing-imaging process while satisfying the equivariant imaging prior.
2 code implementations • 15 May 2023 • Yuanzhi Zhu, Kai Zhang, Jingyun Liang, JieZhang Cao, Bihan Wen, Radu Timofte, Luc van Gool
Although diffusion models have shown impressive performance for high-quality image synthesis, their potential to serve as a generative denoiser prior to the plug-and-play IR methods remains to be further explored.
no code implementations • 30 Apr 2023 • Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis, Radu Timofte, Martin Danelljan, Luc van Gool
Thus, by independently sampling a variant for each gene and combining them into the final latent vector, our approach can represent a vast number of unique latent samples from a compact set of learnable parameters.
2 code implementations • 28 Apr 2023 • Zhuyun Zhou, Zongwei Wu, Danda Pani Paudel, Rémi Boutteau, Fan Yang, Luc van Gool, Radu Timofte, Dominique Ginhac
Subsequently, we devise EmoFormer, a novel network able to exploit the event data.
no code implementations • 27 Apr 2023 • Yasaman Haghighi, Suryansh Kumar, Jean-Philippe Thiran, Luc van Gool
Visual Simultaneous Localization and Mapping (vSLAM) is a widely used technique in robotics and computer vision that enables a robot to create a map of an unfamiliar environment using a camera sensor while simultaneously tracking its position over time.
1 code implementation • ICCV 2023 • Suman Saha, Lukas Hoyer, Anton Obukhov, Dengxin Dai, Luc van Gool
EDAPS significantly improves the state-of-the-art performance for panoptic segmentation UDA by a large margin of 20% on SYNTHIA-to-Cityscapes and even 72% on the more challenging SYNTHIA-to-Mapillary Vistas.
Ranked #1 on Domain Adaptation on Panoptic SYNTHIA-to-Mapillary
3 code implementations • 26 Apr 2023 • Lukas Hoyer, Dengxin Dai, Luc van Gool
As previous UDA&DG semantic segmentation methods are mostly based on outdated networks, we benchmark more recent architectures, reveal the potential of Transformers, and design the DAFormer network tailored for UDA&DG.
1 code implementation • CVPR 2023 • Guolei Sun, Zhaochong An, Yun Liu, Ce Liu, Christos Sakaridis, Deng-Ping Fan, Luc van Gool
We further advance the frontier of this field by systematically studying a new challenge named indiscernible object counting (IOC), the goal of which is to count objects that are blended with respect to their surroundings.
1 code implementation • 21 Apr 2023 • Deng-Ping Fan, Ge-Peng Ji, Peng Xu, Ming-Ming Cheng, Christos Sakaridis, Luc van Gool
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive objects exhibiting camouflage.
no code implementations • 18 Apr 2023 • Han Yao Choong, Suryansh Kumar, Luc van Gool
As a result, in this work, we take the privilege to perform an early exploration of applying a quantum computing algorithm to this important image enhancement problem, i. e., SISR.
no code implementations • CVPR 2023 • Qingsen Yan, Song Zhang, Weiye Chen, Hao Tang, Yu Zhu, Jinqiu Sun, Luc van Gool, Yanning Zhang
In this work, we propose a novel semi-supervised approach to realize few-shot HDR imaging via two stages of training, called SSHDR.
no code implementations • 12 Apr 2023 • Ge-Peng Ji, Deng-Ping Fan, Peng Xu, Ming-Ming Cheng, BoWen Zhou, Luc van Gool
Segmenting anything is a ground-breaking step toward artificial general intelligence, and the Segment Anything Model (SAM) greatly fosters the foundation models for computer vision.
1 code implementation • 11 Apr 2023 • Xue-Jing Luo, Shuo Wang, Zongwei Wu, Christos Sakaridis, Yun Cheng, Deng-Ping Fan, Luc van Gool
Specifically, we leverage the latent diffusion model to synthesize salient objects in camouflaged scenes, while using the zero-shot image classification ability of the Contrastive Language-Image Pre-training (CLIP) model to prevent synthesis failures and ensure the synthesized object aligns with the input prompt.
2 code implementations • ICCV 2023 • Erik Sandström, Yue Li, Luc van Gool, Martin R. Oswald
We propose a dense neural simultaneous localization and mapping (SLAM) approach for monocular RGBD input which anchors the features of a neural scene representation in a point cloud that is iteratively generated in an input-dependent data-driven manner.
no code implementations • 3 Apr 2023 • Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool
One of the most common and useful representation of such an understanding is done in the form of BEV lane graphs.
no code implementations • CVPR 2023 • Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Luc van Gool
Accordingly, we introduce an approach that performs continuous modeling of per-pixel depth, where we can predict and reason about the per-pixel depth and its distribution.
no code implementations • CVPR 2023 • Nishant Jain, Suryansh Kumar, Luc van Gool
Extensive evaluation of our approach on the popular benchmark dataset, such as Tanks and Temples, shows substantial improvement in view synthesis results compared to the prior art.
no code implementations • CVPR 2023 • Guofeng Mei, Hao Tang, Xiaoshui Huang, Weijie Wang, Juan Liu, Jian Zhang, Luc van Gool, Qiang Wu
Deep point cloud registration methods face challenges to partial overlaps and rely on labeled data.
1 code implementation • 22 Mar 2023 • Mohamad Shahbazi, Evangelos Ntavelis, Alessio Tonioni, Edo Collins, Danda Pani Paudel, Martin Danelljan, Luc van Gool
Pose-conditioned convolutional generative models struggle with high-quality 3D-consistent image generation from single-view datasets, due to their lack of sufficient 3D priors.
no code implementations • 21 Mar 2023 • Kamil Adamczewski, Christos Sakaridis, Vaishakh Patil, Luc van Gool
Lidar is a vital sensor for estimating the depth of a scene.
1 code implementation • ICCV 2023 • Bin Xia, Yulun Zhang, Shiyin Wang, Yitong Wang, Xinglong Wu, Yapeng Tian, Wenming Yang, Luc van Gool
Diffusion model (DM) has achieved SOTA performance by modeling the image synthesis process into a sequential application of a denoising network.
no code implementations • ICCV 2023 • Zixiang Zhao, Jiangshe Zhang, Xiang Gu, Chengli Tan, Shuang Xu, Yulun Zhang, Radu Timofte, Luc van Gool
Then, the extracted features are mapped to the spherical space to complete the separation of private features and the alignment of shared features.
no code implementations • CVPR 2023 • Hao Tang, Zhenyu Zhang, Humphrey Shi, Bo Li, Ling Shao, Nicu Sebe, Radu Timofte, Luc van Gool
We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for the challenging graph-constrained house generation task.
3 code implementations • ICCV 2023 • Zixiang Zhao, Haowen Bai, Yuanzhi Zhu, Jiangshe Zhang, Shuang Xu, Yulun Zhang, Kai Zhang, Deyu Meng, Radu Timofte, Luc van Gool
To leverage strong generative priors and address challenges such as unstable training and lack of interpretability for GAN-based generative methods, we propose a novel fusion algorithm based on the denoising diffusion probabilistic model (DDPM).
1 code implementation • ICCV 2023 • David Bruggemann, Christos Sakaridis, Tim Brödermann, Luc van Gool
We investigate normal-to-adverse condition model adaptation for semantic segmentation, whereby image-level correspondences are available in the target domain.
Ranked #1 on Source-Free Domain Adaptation on Cityscapes to ACDC
2 code implementations • 7 Mar 2023 • Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, Luc van Gool
We present TrafficBots, a multi-agent policy built upon motion prediction and end-to-end driving, and based on TrafficBots we obtain a world model tailored for the planning module of autonomous vehicles.
1 code implementation • 7 Mar 2023 • Nick Bührer, Zhejun Zhang, Alexander Liniger, Fisher Yu, Luc van Gool
To this end, we propose a safe model-free RL algorithm with a novel multiplicative value function consisting of a safety critic and a reward critic.
1 code implementation • CVPR 2023 • Yawei Li, Yuchen Fan, Xiaoyu Xiang, Denis Demandolx, Rakesh Ranjan, Radu Timofte, Luc van Gool
The aim of this paper is to propose a mechanism to efficiently and explicitly model image hierarchies in the global, regional, and local range for image restoration.
Ranked #1 on Image Defocus Deblurring on DPD (Dual-view)
2 code implementations • 13 Feb 2023 • Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Luc van Gool
While state-of-the-art deep neural network methods for SIDP learn the scene depth from images in a supervised setting, they often overlook the invaluable invariances and priors in the rigid scene space, such as the regularity of the scene.
Ranked #21 on Monocular Depth Estimation on NYU-Depth V2
2 code implementations • 2 Feb 2023 • Jiahua Dong, Hongliu Li, Yang Cong, Gan Sun, Yulun Zhang, Luc van Gool
These issues render global model to undergo catastrophic forgetting on old categories, when local clients receive new categories consecutively under limited memory of storing old categories.
no code implementations • 22 Jan 2023 • Razvan-George Pasca, Alexey Gavryushin, Muhammad Hamza, Yen-Ling Kuo, Kaichun Mo, Luc van Gool, Otmar Hilliges, Xi Wang
This task requires an understanding of the spatio-temporal context formed by past actions on objects, coined action context.
no code implementations • CVPR 2023 • Lei Sun, Christos Sakaridis, Jingyun Liang, Peng Sun, JieZhang Cao, Kai Zhang, Qi Jiang, Kaiwei Wang, Luc van Gool
The performance of video frame interpolation is inherently correlated with the ability to handle motion in the input scene.
no code implementations • ICCV 2023 • Goutam Bhat, Michaël Gharbi, Jiawen Chen, Luc van Gool, Zhihao Xia
Extensive experiments on real and synthetic data show that, despite only using noisy bursts during training, models trained with our self-supervised strategy match, and sometimes surpass, the quality of fully-supervised baselines trained with synthetic data or weakly-paired ground-truth.
no code implementations • CVPR 2023 • Rui Gong, Qin Wang, Martin Danelljan, Dengxin Dai, Luc van Gool
Unsupervised domain adaptation (UDA) for semantic segmentation aims at improving the model performance on the unlabeled target domain by leveraging a labeled source domain.
1 code implementation • 22 Dec 2022 • Christoph Mayer, Martin Danelljan, Ming-Hsuan Yang, Vittorio Ferrari, Luc van Gool, Alina Kuznetsova
Our approach achieves a 4x faster run-time in case of 10 concurrent objects compared to tracking each object independently and outperforms existing single object trackers on our new benchmark.
no code implementations • 14 Dec 2022 • Rui Gong, Qin Wang, Dengxin Dai, Luc van Gool
Thus, we aim to relieve this need on a large number of real data, and explore the one-shot unsupervised sim-to-real domain adaptation (OSUDA) and generalization (OSDG) problem, where only one real-world data sample is available.
1 code implementation • 10 Dec 2022 • Bowen Yin, Xuying Zhang, Qibin Hou, Bo-Yuan Sun, Deng-Ping Fan, Luc van Gool
How to identify and segment camouflaged objects from the background is challenging.
1 code implementation • ICCV 2023 • Zongwei Wu, Danda Pani Paudel, Deng-Ping Fan, Jingjing Wang, Shuo Wang, Cédric Demonceaux, Radu Timofte, Luc van Gool
In this work, we adapt such depth inference models for object segmentation using the objects' "pop-out" prior in 3D.
1 code implementation • CVPR 2023 • JieZhang Cao, Qin Wang, Yongqin Xian, Yawei Li, Bingbing Ni, Zhiming Pi, Kai Zhang, Yulun Zhang, Radu Timofte, Luc van Gool
We explicitly design an implicit attention network to learn the ensemble weights for the nearby local features.
no code implementations • CVPR 2023 • Muhammad Ferjad Naeem, Muhammad Gul Zain Ali Khan, Yongqin Xian, Muhammad Zeshan Afzal, Didier Stricker, Luc van Gool, Federico Tombari
Our proposed model, I2MVFormer, learns multi-view semantic embeddings for zero-shot image classification with these class views.
1 code implementation • ICCV 2023 • Nikola Popovic, Danda Pani Paudel, Luc van Gool
In this work, we aim to leverage the geometric prior of Manhattan scenes to improve the implicit neural radiance field representations.
1 code implementation • CVPR 2023 • Lukas Hoyer, Dengxin Dai, Haoran Wang, Luc van Gool
MIC significantly improves the state-of-the-art performance across the different recognition tasks for synthetic-to-real, day-to-nighttime, and clear-to-adverse-weather UDA.
1 code implementation • 30 Nov 2022 • Bin Xia, Yulun Zhang, Yitong Wang, Yapeng Tian, Wenming Yang, Radu Timofte, Luc van Gool
It consists of a knowledge distillation based implicit degradation estimator network (KD-IDE) and an efficient SR network.
3 code implementations • CVPR 2023 • Zixiang Zhao, Haowen Bai, Jiangshe Zhang, Yulun Zhang, Shuang Xu, Zudi Lin, Radu Timofte, Luc van Gool
We then introduce a dual-branch Transformer-CNN feature extractor with Lite Transformer (LT) blocks leveraging long-range attention to handle low-frequency global features and Invertible Neural Networks (INN) blocks focusing on extracting high-frequency local information.
no code implementations • ICCV 2023 • Shengqu Cai, Eric Ryan Chan, Songyou Peng, Mohamad Shahbazi, Anton Obukhov, Luc van Gool, Gordon Wetzstein
Scene extrapolation -- the idea of generating novel views by flying into a given image -- is a promising, yet challenging task.
Ranked #1 on Perpetual View Generation on LHQ
no code implementations • 14 Nov 2022 • Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool
On the one hand, the proposed method learns to segment these planar hulls from the labeled data.
1 code implementation • 13 Nov 2022 • Ren Yang, Radu Timofte, Luc van Gool
In this paper, we propose an Advanced Learned Video Compression (ALVC) approach with the in-loop frame prediction module, which is able to effectively predict the target frame from the previously compressed frames, without consuming any bit-rate.
no code implementations • 8 Nov 2022 • Andrey Ignatov, Anastasia Sycheva, Radu Timofte, Yu Tseng, Yu-Syuan Xu, Po-Hsiang Yu, Cheng-Ming Chiang, Hsien-Kai Kuo, Min-Hung Chen, Chia-Ming Cheng, Luc van Gool
While neural networks-based photo processing solutions can provide a better image quality compared to the traditional ISP systems, their application to mobile devices is still very limited due to their very high computational complexity.
1 code implementation • 8 Nov 2022 • Andrey Ignatov, Grigory Malivenko, Radu Timofte, Yu Tseng, Yu-Syuan Xu, Po-Hsiang Yu, Cheng-Ming Chiang, Hsien-Kai Kuo, Min-Hung Chen, Chia-Ming Cheng, Luc van Gool
The increased importance of mobile photography created a need for fast and performant RAW image processing pipelines capable of producing good visual results in spite of the mobile camera sensor limitations.
1 code implementation • 30 Oct 2022 • Hanqing Wang, Wei Liang, Luc van Gool, Wenguan Wang
With the emergence of varied visual navigation tasks (e. g, image-/object-/audio-goal and vision-language navigation) that specify the target in different ways, the community has made appealing advances in training specialized agents capable of handling individual navigation tasks well.
no code implementations • 28 Oct 2022 • Nicola Marinello, Marc Proesmans, Luc van Gool
We start from an off-the-shelf 3D object detector, and apply a tracking mechanism where objects are matched by an affinity score computed on local object feature embeddings and motion descriptors.
1 code implementation • 27 Oct 2022 • Ge-Peng Ji, Mingcheng Zhuge, Dehong Gao, Deng-Ping Fan, Christos Sakaridis, Luc van Gool
We present a masked vision-language transformer (MVLT) for fashion-specific multi-modal representation.
no code implementations • 20 Oct 2022 • Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc van Gool, Alain Pagani, Didier Stricker, Muhammad Zeshan Afzal
CAPE learns to identify this structure and propagates knowledge between them to learn class embedding for all seen and unseen compositions.
no code implementations • 14 Oct 2022 • Berk Kaya, Suryansh Kumar, Carlos Oliveira, Vittorio Ferrari, Luc van Gool
The proposed approach in this paper exploits the benefit of uncertainty modeling in a deep neural network for a reliable fusion of photometric stereo (PS) and multi-view stereo (MVS) network predictions.
no code implementations • 13 Oct 2022 • Menelaos Kanakis, Thomas E. Huang, David Bruggemann, Fisher Yu, Luc van Gool
In this paper, we find that jointly training a dense prediction (target) task with a self-supervised (auxiliary) task can consistently improve the performance of the target task, while eliminating the need for labeling auxiliary tasks.
Ranked #104 on Semantic Segmentation on NYU Depth v2
1 code implementation • 10 Oct 2022 • Yitong Xia, Hao Tang, Radu Timofte, Luc van Gool
NeRFmm is the Neural Radiance Fields (NeRF) that deal with Joint Optimization tasks, i. e., reconstructing real-world scenes and registering camera parameters simultaneously.
no code implementations • 9 Oct 2022 • Nishant Jain, Suryansh Kumar, Luc van Gool
Although recently proposed Mip-NeRF could handle multi-scale imaging problems with NeRF, it cannot handle camera pose estimation error.
2 code implementations • 2 Oct 2022 • Bin Xia, Yulun Zhang, Yitong Wang, Yapeng Tian, Wenming Yang, Radu Timofte, Luc van Gool
In this study, we reconsider components in binary convolution, such as residual connection, BatchNorm, activation function, and structure, for IR tasks.
1 code implementation • 30 Sep 2022 • Anton Obukhov, Mikhail Usvyatsov, Christos Sakaridis, Konrad Schindler, Luc van Gool
Learning neural fields has been an active topic in deep learning research, focusing, among other issues, on finding more compact and easy-to-fit representations.
1 code implementation • 30 Sep 2022 • Hui Wei, Hao Tang, Xuemei Jia, Zhixiang Wang, Hanxun Yu, Zhubo Li, Shin'ichi Satoh, Luc van Gool, Zheng Wang
Building upon this foundation, we uncover the pervasive role of artifacts carrying adversarial perturbations in the physical world.
1 code implementation • 28 Sep 2022 • Yifan Lu, Gurkirt Singh, Suman Saha, Luc van Gool
We propose a novel domain adaptive action detection approach and a new adaptation protocol that leverages the recent advancements in image-level unsupervised domain adaptation (UDA) techniques and handle vagaries of instance-level video data.
no code implementations • 21 Sep 2022 • Muhammad Ferjad Naeem, Yongqin Xian, Luc van Gool, Federico Tombari
In order to distill discriminative visual words from noisy documents, we introduce a new cross-modal attention module that learns fine-grained interactions between image patches and document words.
no code implementations • 6 Sep 2022 • Gurkirt Singh, Vasileios Choutas, Suman Saha, Fisher Yu, Luc van Gool
Current methods for spatiotemporal action tube detection often extend a bounding box proposal at a given keyframe into a 3D temporal cuboid and pool features from nearby frames.
no code implementations • 25 Aug 2022 • JieZhang Cao, Qin Wang, Jingyun Liang, Yulun Zhang, Kai Zhang, Radu Timofte, Luc van Gool
To this end, we propose a new multi-scale refined optical flow-guided video denoising method, which is more robust to different noise levels.
Ranked #1 on Video Denoising on VideoLQ
no code implementations • 18 Aug 2022 • Janis Postels, Martin Danelljan, Luc van Gool, Federico Tombari
In contrast to prior work, we approach this problem by generating samples from the original data distribution given full knowledge about the perturbed distribution and the noise model.
1 code implementation • 14 Aug 2022 • Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha, Christoph Mayer, Akshay Dudhane, Martin Danelljan, Hisham Cholakkal, Salman Khan, Luc van Gool, Fahad Shahbaz Khan
While being greatly benefiting to the tracking research, existing benchmarks do not pose the same difficulty as before with recent trackers achieving higher performance mainly due to (i) the introduction of more sophisticated transformers-based methods and (ii) the lack of diverse scenarios with adverse visibility such as, severe weather conditions, camouflage and imaging effects.
1 code implementation • 25 Jul 2022 • JieZhang Cao, Jingyun Liang, Kai Zhang, Yawei Li, Yulun Zhang, Wenguan Wang, Luc van Gool
Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref) images to super-resolve low-resolution (LR) images.
1 code implementation • 21 Jul 2022 • JieZhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, Luc van Gool
These issues can be alleviated by a cascade of three separate sub-tasks, including video deblurring, frame interpolation, and super-resolution, which, however, would fail to capture the spatial and temporal correlations among video sequences.
1 code implementation • 21 Jul 2022 • Guolei Sun, Yun Liu, Hao Tang, Ajad Chhatkuli, Le Zhang, Luc van Gool
The essence of video semantic segmentation (VSS) is how to leverage temporal information for prediction.
1 code implementation • 14 Jul 2022 • David Bruggemann, Christos Sakaridis, Prune Truong, Luc van Gool
Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UDA) for the semantic segmentation of such images.
Ranked #1 on Semantic Segmentation on Dark Zurich
no code implementations • 13 Jul 2022 • Suryansh Kumar, Luc van Gool
Besides that, the paper provides insights into the NRSfM factorization -- both in terms of shape and motion -- and is the first approach to show the benefit of single rotation averaging for NRSfM.
1 code implementation • 5 Jul 2022 • Jialun Pei, Tianyang Cheng, Deng-Ping Fan, He Tang, Chuanbo Chen, Luc van Gool
We present OSFormer, the first one-stage transformer framework for camouflaged instance segmentation (CIS).
1 code implementation • 3 Jul 2022 • Kevin Ta, David Bruggemann, Tim Brödermann, Christos Sakaridis, Luc van Gool
As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research.
1 code implementation • 30 Jun 2022 • Tim Broedermann, Christos Sakaridis, Dengxin Dai, Luc van Gool
Besides standard cameras, autonomous vehicles typically include multiple additional sensors, such as lidars and radars, which help acquire richer information for perceiving the content of the driving scene.
Ranked #1 on 2D Object Detection on Clear Weather
1 code implementation • 29 Jun 2022 • Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Hao Tang, Gordon Wetzstein, Leonidas Guibas, Luc van Gool, Radu Timofte
Generative models have emerged as an essential building block for many image synthesis and editing tasks.
1 code implementation • CVPR 2022 • Tao Sun, Mattia Segu, Janis Postels, Yuxuan Wang, Luc van Gool, Bernt Schiele, Federico Tombari, Fisher Yu
Adapting to a continuously evolving environment is a safety-critical challenge inevitably faced by all autonomous driving systems.
1 code implementation • CVPR 2023 • Bin Xia, Jingwen He, Yulun Zhang, Yitong Wang, Yapeng Tian, Wenming Yang, Luc van Gool
In SSL, we design pruning schemes for several key components in VSR models, including residual blocks, recurrent networks, and upsampling networks.
1 code implementation • 13 Jun 2022 • Wouter Van Gansbeke, Simon Vandenhende, Luc van Gool
This paper presents MaskDistill: a novel framework for unsupervised semantic segmentation based on three key ideas.
Ranked #4 on Unsupervised Semantic Segmentation on PASCAL VOC 2012 val (using extra training data)
3 code implementations • 5 Jun 2022 • Jingyun Liang, Yuchen Fan, Xiaoyu Xiang, Rakesh Ranjan, Eddy Ilg, Simon Green, JieZhang Cao, Kai Zhang, Radu Timofte, Luc van Gool
Specifically, RVRT divides the video into multiple clips and uses the previously inferred clip feature to estimate the subsequent clip feature.
no code implementations • 3 Jun 2022 • Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool
It has since become a trend to use these five characteristics as a sufficient test, to determine whether or not gradient obfuscation is the main source of robustness.
3 code implementations • 30 May 2022 • Peng Zheng, Huazhu Fu, Deng-Ping Fan, Qi Fan, Jie Qin, Yu-Wing Tai, Chi-Keung Tang, Luc van Gool
In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in natural scenes.
Ranked #1 on Co-Salient Object Detection on CoCA
1 code implementation • 25 May 2022 • Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, Luc van Gool
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD).
1 code implementation • 20 May 2022 • Jing Lin, Xiaowan Hu, Yuanhao Cai, Haoqian Wang, Youliang Yan, Xueyi Zou, Yulun Zhang, Luc van Gool
On the other hand, we equip the sequence-to-sequence model with an unsupervised optical flow estimator to maximize its potential.
Ranked #2 on Video Enhancement on MFQE v2
1 code implementation • 20 May 2022 • Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc van Gool
In coded aperture snapshot spectral compressive imaging (CASSI) systems, hyperspectral image (HSI) reconstruction methods are employed to recover the spatial-spectral signal from a compressed measurement.
Ranked #1 on Spectral Reconstruction on Real HSI
1 code implementation • CVPR 2022 • Yawei Li, Kamil Adamczewski, Wen Li, Shuhang Gu, Radu Timofte, Luc van Gool
The proposed approach provides a new way to compare different methods, namely how well they behave compared with random pruning.
1 code implementation • 11 May 2022 • Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Luc van Gool
Within the proposed benchmark, we explore some commonly known essentials of standard continual learning.
2 code implementations • 11 May 2022 • Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang
The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.
1 code implementation • 27 Apr 2022 • Lukas Hoyer, Dengxin Dai, Luc van Gool
Therefore, we propose HRDA, a multi-resolution training approach for UDA, that combines the strengths of small high-resolution crops to preserve fine segmentation details and large low-resolution crops to capture long-range context dependencies with a learned scale attention, while maintaining a manageable GPU memory footprint.
Ranked #3 on Semantic Segmentation on GTAV-to-Cityscapes Labels
3 code implementations • 17 Apr 2022 • Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Radu Timofte, Luc van Gool
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image to its hyperspectral image (HSI).
Ranked #1 on Spectral Reconstruction on ARAD-1K
1 code implementation • 13 Apr 2022 • Edoardo Mello Rella, Ajad Chhatkuli, Ender Konukoglu, Luc van Gool
With neural networks, several other variations and training principles have been proposed with the goal to represent all classes of shapes.
1 code implementation • CVPR 2022 • Guolei Sun, Yun Liu, Henghui Ding, Min Wu, Luc van Gool
Specifically, we uniformly sample certain frames from the video and extract global contextual prototypes by k-means.
1 code implementation • 7 Apr 2022 • Erik Sandström, Martin R. Oswald, Suryansh Kumar, Silvan Weder, Fisher Yu, Cristian Sminchisescu, Luc van Gool
Multi-sensor depth fusion is able to substantially improve the robustness and accuracy of 3D reconstruction methods, but existing techniques are not robust enough to handle sensors which operate with diverse value ranges as well as noise and outlier statistics.
1 code implementation • CVPR 2022 • Vaishakh Patil, Christos Sakaridis, Alexander Liniger, Luc van Gool
We focus on the supervised setup, in which ground-truth depth is available only at training time.
Ranked #6 on Depth Estimation on NYU-Depth V2
1 code implementation • CVPR 2022 • Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis, Radu Timofte, Martin Danelljan, Luc van Gool
Positional encodings have enabled recent works to train a single adversarial network that can generate images of different scales.
no code implementations • 5 Apr 2022 • Jose L. Vazquez, Alexander Liniger, Wilko Schwarting, Daniela Rus, Luc van Gool
Fundamental to the success of our method is the design of a novel multi-agent policy network that can steer a vehicle given the state of the surrounding agents and the map information.
no code implementations • 4 Apr 2022 • Liqian Ma, Lingjie Liu, Christian Theobalt, Luc van Gool
In addition, DDP is computationally more efficient than previous dense pose estimation methods, and it reduces jitters when applied to a video sequence, which is a problem plaguing the previous methods.
no code implementations • 4 Apr 2022 • Liqian Ma, Stamatios Georgoulis, Xu Jia, Luc van Gool
The ability to make educated predictions about their surroundings, and associate them with certain confidence, is important for intelligent systems, like autonomous vehicles and robots.
1 code implementation • CVPR 2022 • Hanqing Wang, Wei Liang, Jianbing Shen, Luc van Gool, Wenguan Wang
Since the rise of vision-language navigation (VLN), great progress has been made in instruction following -- building a follower to navigate environments under the guidance of instructions.
1 code implementation • CVPR 2022 • Martin Hahner, Christos Sakaridis, Mario Bijelic, Felix Heide, Fisher Yu, Dengxin Dai, Luc van Gool
Due to the difficulty of collecting and annotating training data in this setting, we propose a physically based method to simulate the effect of snowfall on real clear-weather LiDAR point clouds.
Ranked #1 on 3D Object Detection on Heavy Snowfall
1 code implementation • CVPR 2022 • Tianfei Zhou, Wenguan Wang, Ender Konukoglu, Luc van Gool
Prevalent semantic segmentation solutions, despite their different network designs (FCN based or attention based) and mask decoding strategies (parametric softmax based or pixel-query based), can be placed in one category, by considering the softmax weights or query vectors as learnable class prototypes.
4 code implementations • 27 Mar 2022 • Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou, Deng-Ping Fan, Kai Zhao, Geng Chen, Luc van Gool
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era.
Ranked #2 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
no code implementations • 25 Mar 2022 • Ritika Chakraborty, Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool
However, multi-conditional image generation is a very challenging problem due to the heterogeneity and the sparsity of the (in practice) available conditioning labels.
2 code implementations • CVPR 2022 • Qin Wang, Olga Fink, Luc van Gool, Dengxin Dai
However, real-world machine perception systems are running in non-stationary and continually changing environments where the target domain distribution can change over time.
2 code implementations • 24 Mar 2022 • Kai Zhang, Yawei Li, Jingyun Liang, JieZhang Cao, Yulun Zhang, Hao Tang, Deng-Ping Fan, Radu Timofte, Luc van Gool
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, such as additive white Gaussian noise (AWGN), JPEG compression noise and camera sensor noise, and a general-purpose blind denoising method for real images remains unsolved.
Ranked #1 on Image Denoising on urban100 sigma15
2 code implementations • 21 Mar 2022 • Matthieu Paul, Martin Danelljan, Christoph Mayer, Luc van Gool
We infer a bounding box from the segmentation mask, validate our tracker on challenging tracking datasets and achieve the new state of the art on LaSOT with a success AUC score of 69. 7%.
1 code implementation • CVPR 2022 • Christoph Mayer, Martin Danelljan, Goutam Bhat, Matthieu Paul, Danda Pani Paudel, Fisher Yu, Luc van Gool
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function.
Ranked #21 on Visual Object Tracking on LaSOT (Precision metric)
no code implementations • 20 Mar 2022 • Ardhendu Shekhar Tripathi, Martin Danelljan, Samarth Shukla, Radu Timofte, Luc van Gool
We propose a trainable Image Signal Processing (ISP) framework that produces DSLR quality images given RAW images captured by a smartphone.
3 code implementations • CVPR 2022 • Ozan Unal, Dengxin Dai, Luc van Gool
Densely annotating LiDAR point clouds remains too expensive and time-consuming to keep up with the ever growing volume of data.
Ranked #2 on 3D Semantic Segmentation on ScribbleKITTI
1 code implementation • ICLR 2022 • Edoardo Mello Rella, Ajad Chhatkuli, Yun Liu, Ender Konukoglu, Luc van Gool
One of the key problems in boundary detection is the label representation, which typically leads to class imbalance and, as a consequence, to thick boundaries that require non-differential post-processing steps to be thinned.
no code implementations • 13 Mar 2022 • Feiyu Wang, Qin Wang, Wen Li, Dong Xu, Luc van Gool
Benefited from this new perspective, we first propose a new deep semi-supervised learning framework called Semi-supervised Learning by Empirical Distribution Alignment (SLEDA), in which existing technologies from the domain adaptation community can be readily used to address the semi-supervised learning problem through reducing the empirical distribution distance between labeled and unlabeled data.
1 code implementation • 9 Mar 2022 • Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i. e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement.
Ranked #2 on Spectral Reconstruction on Real HSI
1 code implementation • CVPR 2022 • Prune Truong, Martin Danelljan, Fisher Yu, Luc van Gool
We propose Probabilistic Warp Consistency, a weakly-supervised learning objective for semantic matching.
1 code implementation • 7 Mar 2022 • Abhishek Jha, Badri N. Patro, Luc van Gool, Tinne Tuytelaars
In this paper, we propose a novel regularization for VQA models, Constrained Optimization using Barlow's theory (COB), that improves the information content of the joint space by minimizing the redundancy.
1 code implementation • 7 Mar 2022 • Menelaos Kanakis, Simon Maurer, Matteo Spallanzani, Ajad Chhatkuli, Luc van Gool
Efficient detection and description of geometric regions in images is a prerequisite in visual systems for localization and mapping.
2 code implementations • CVPR 2022 • Xiaowan Hu, Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc van Gool
On the one hand, the proposed HR spatial-spectral attention module with its efficient feature fusion provides continuous and fine pixel-level features.
Ranked #5 on Spectral Reconstruction on Real HSI
no code implementations • CVPR 2022 • Berk Kaya, Suryansh Kumar, Carlos Oliveira, Vittorio Ferrari, Luc van Gool
At each pixel, our approach either selects or discards deep-PS and deep-MVS network prediction depending on the prediction uncertainty measure.
2 code implementations • 26 Feb 2022 • Shengqu Cai, Anton Obukhov, Dengxin Dai, Luc van Gool
We propose a pipeline to generate Neural Radiance Fields~(NeRF) of an object or a scene of a specific class, conditioned on a single input image.
no code implementations • CVPR 2022 • Jan-Nico Zaech, Alexander Liniger, Martin Danelljan, Dengxin Dai, Luc van Gool
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
no code implementations • 3 Feb 2022 • Dario Fuoli, Martin Danelljan, Radu Timofte, Luc van Gool
Our DAP aligns and integrates information from the recurrent state into the current frame prediction.
1 code implementation • 28 Jan 2022 • Jingyun Liang, JieZhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc van Gool
Besides, parallel warping is used to further fuse information from neighboring frames by parallel feature warping.
Ranked #1 on Deblurring on BASED
6 code implementations • 27 Jan 2022 • Zudi Lin, Prateek Garg, Atmadeep Banerjee, Salma Abdel Magid, Deqing Sun, Yulun Zhang, Luc van Gool, Donglai Wei, Hanspeter Pfister
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight.
3 code implementations • CVPR 2022 • Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, Luc van Gool
In this work, we propose RePaint: A Denoising Diffusion Probabilistic Model (DDPM) based inpainting approach that is applicable to even extreme masks.
1 code implementation • ICLR 2022 • Mohamad Shahbazi, Martin Danelljan, Danda Pani Paudel, Luc van Gool
On the contrary, we observe that class-conditioning causes mode collapse in limited data settings, where unconditional learning leads to satisfactory generative ability.
1 code implementation • 11 Jan 2022 • Niclas Vödisch, Ozan Unal, Ke Li, Luc van Gool, Dengxin Dai
In this work, we take a new route to learn to optimize the LiDAR beam configuration for a given application.
1 code implementation • 6 Jan 2022 • Jing Lin, Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Youliang Yan, Xueyi Zou, Henghui Ding, Yulun Zhang, Radu Timofte, Luc van Gool
Exploiting similar and sharper scene patches in spatio-temporal neighborhoods is critical for video deblurring.
Ranked #1 on Deblurring on DVD
no code implementations • CVPR 2022 • Arun Balajee Vasudevan, Dengxin Dai, Luc van Gool
Specifically, for this study, we investigate binaural sounds and image data in isolation.
1 code implementation • CVPR 2022 • Shengqu Cai, Anton Obukhov, Dengxin Dai, Luc van Gool
We propose a pipeline to generate Neural Radiance Fields (NeRF) of an object or a scene of a specific class, conditioned on a single input image.