1 code implementation • 27 Nov 2023 • Wentao Chao, Fuqing Duan, Xuechun Wang, Yingqian Wang, Guanghui Wang
Despite this complexity, mainstream LF image SR methods typically adopt a deterministic approach, generating only a single output supervised by pixel-wise loss functions.
1 code implementation • 28 May 2023 • Wentao Chao, Fuqing Duan, Xuechun Wang, Yingqian Wang, Guanghui Wang
To address this issue and achieve a better trade-off between accuracy and efficiency, we propose an occlusion-aware cascade cost volume for LF depth (disparity) estimation.
1 code implementation • 23 May 2023 • Shitian He, Huanxin Zou, Yingqian Wang, Boyang Li, Xu Cao, Ning Jing
In this paper, we make the first attempt to achieve RS object detection with single point supervision, and propose a PSOD method tailored for RS images.
1 code implementation • 20 Apr 2023 • Yingqian Wang, Longguang Wang, Zhengyu Liang, Jungang Yang, Radu Timofte, Yulan Guo
In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4.
1 code implementation • ICCV 2023 • Boyang Li, Yingqian Wang, Longguang Wang, Fei Zhang, Ting Liu, Zaiping Lin, Wei An, Yulan Guo
The core idea of this work is to recover the per-pixel mask of each target from the given single point label by using clustering approaches, which looks simple but is indeed challenging since targets are always insalient and accompanied with background clutters.
1 code implementation • CVPR 2023 • Xinyi Ying, Li Liu, Yingqian Wang, Ruojing Li, Nuo Chen, Zaiping Lin, Weidong Sheng, Shilin Zhou
Interestingly, during the training phase supervised by point labels, we discover that CNNs first learn to segment a cluster of pixels near the targets, and then gradually converge to predict groundtruth point labels.
1 code implementation • 31 Mar 2023 • Zhaoxu Li, Yingqian Wang, Chao Xiao, Qiang Ling, Zaiping Lin, Wei An
Trained on a set of anomaly-free hyperspectral images with random masks, our network can learn the spatial context characteristics between anomalies and background in an unsupervised way.
1 code implementation • ICCV 2023 • Zhengyu Liang, Yingqian Wang, Longguang Wang, Jungang Yang, Shilin Zhou, Yulan Guo
Exploiting spatial-angular correlation is crucial to light field (LF) image super-resolution (SR), but is highly challenging due to its non-local property caused by the disparities among LF images.
1 code implementation • 28 Sep 2022 • Tianhao Wu, Boyang Li, Yihang Luo, Yingqian Wang, Chao Xiao, Ting Liu, Jungang Yang, Wei An, Yulan Guo
Due to the extremely large image coverage area (e. g., thousands square kilometers), candidate targets in these images are much smaller, dimer, more changeable than those targets observed by aerial-based and land-based imaging devices.
2 code implementations • 20 Aug 2022 • Wentao Chao, Xuechun Wang, Yingqian Wang, Guanghui Wang, Fuqing Duan
However, the disparity map is only a sub-space projection (i. e., an expectation) of the disparity distribution, which is essential for models to learn.
3 code implementations • 13 Jun 2022 • Yingqian Wang, Zhengyu Liang, Longguang Wang, Jungang Yang, Wei An, Yulan Guo
In our method, a practical LF degradation model is developed to formulate the degradation process of real LF images.
no code implementations • 20 Apr 2022 • Longguang Wang, Yulan Guo, Yingqian Wang, Juncheng Li, Shuhang Gu, Radu Timofte
In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new solutions and results.
1 code implementation • CVPR 2022 • Yingqian Wang, Longguang Wang, Zhengyu Liang, Jungang Yang, Wei An, Yulan Guo
Based on the proposed cost constructor, we develop a deep network for LF depth estimation.
no code implementations • 22 Feb 2022 • Yingqian Wang, Longguang Wang, Gaochang Wu, Jungang Yang, Wei An, Jingyi Yu, Yulan Guo
In this paper, we propose a generic mechanism to disentangle these coupled information for LF image processing.
1 code implementation • 4 Jan 2022 • Xinyi Ying, Yingqian Wang, Longguang Wang, Weidong Sheng, Li Liu, Zaiping Lin, Shilin Zhou
Specifically, motivated by the local motion prior in the spatio-temporal dimension, we propose a local spatio-temporal attention module to perform implicit frame alignment and incorporate the local spatio-temporal information to enhance the local features (especially for small targets).
1 code implementation • CVPR 2022 • Longguang Wang, Xiaoyu Dong, Yingqian Wang, Li Liu, Wei An, Yulan Guo
Since a linear quantizer (i. e., round(*) function) cannot well fit the bell-shaped distributions of weights and activations, many existing methods use pre-defined functions (e. g., exponential function) with learnable parameters to build the quantizer for joint optimization.
1 code implementation • 25 Nov 2021 • Qian Yin, Qingyong Hu, Hao liu, Feng Zhang, Yingqian Wang, Zaiping Lin, Wei An, Yulan Guo
Satellite video cameras can provide continuous observation for a large-scale area, which is important for many remote sensing applications.
no code implementations • 23 Oct 2021 • Yu Mo, Yingqian Wang, Chao Xiao, Jungang Yang, Wei An
Light field (LF) images can be used to improve the performance of image super-resolution (SR) because both angular and spatial information is available.
1 code implementation • 3 Oct 2021 • Feng Zhang, Xueying Wang, Shilin Zhou, Yingqian Wang
Rotated object detection in aerial images has received increasing attention for a wide range of applications.
1 code implementation • 29 Sep 2021 • Juncheng Li, Zehua Pei, Wenjie Li, Guangwei Gao, Longguang Wang, Yingqian Wang, Tieyong Zeng
This is an exhaustive survey of SISR, which can help researchers better understand SISR and inspire more exciting research in this field.
1 code implementation • 17 Aug 2021 • Zhengyu Liang, Yingqian Wang, Longguang Wang, Jungang Yang, Shilin Zhou
With the proposed angular and spatial Transformers, the beneficial information in an LF can be fully exploited and the SR performance is boosted.
1 code implementation • 9 Aug 2021 • Yingqian Wang, Jungang Yang, Yulan Guo, Chao Xiao, Wei An
In this letter, we propose a light field refocusing method to improve the imaging quality of camera arrays.
1 code implementation • 1 Jun 2021 • Boyang Li, Chao Xiao, Longguang Wang, Yingqian Wang, Zaiping Lin, Miao Li, Wei An, Yulan Guo
With the repeated interaction in DNIM, infrared small targets in deep layers can be maintained.
1 code implementation • 31 May 2021 • Ting Liu, Jungang Yang, Boyang Li, Chao Xiao, Yang Sun, Yingqian Wang, Wei An
Considering that different singular values have different importance and should be treated discriminatively, in this paper, we propose a non-convex tensor low-rank approximation (NTLA) method for infrared small target detection.
2 code implementations • CVPR 2021 • Longguang Wang, Yingqian Wang, Xiaoyu Dong, Qingyu Xu, Jungang Yang, Wei An, Yulan Guo
In this paper, we propose an unsupervised degradation representation learning scheme for blind SR without explicit degradation estimation.
no code implementations • 17 Mar 2021 • Shitian He, Huanxin Zou, Yingqian Wang, Runlin Li, Fei Cheng
In this paper, we explore the potential benefits introduced by image SR to ship detection, and propose an end-to-end network named ShipSRDet.
1 code implementation • 27 Jan 2021 • Feng Zhang, Xueying Wang, Shilin Zhou, Yingqian Wang, Yi Hou
Moreover, we introduce a new dataset for multi-class arbitrary-oriented ship detection in remote sensing images at a fixed ground sample distance (GSD) which is named FGSD2021.
1 code implementation • 7 Nov 2020 • Yingqian Wang, Xinyi Ying, Longguang Wang, Jungang Yang, Wei An, Yulan Guo
Although recent years have witnessed the great advances in stereo image super-resolution (SR), the beneficial information provided by binocular systems has not been fully used.
1 code implementation • 16 Sep 2020 • Longguang Wang, Yulan Guo, Yingqian Wang, Zhengfa Liang, Zaiping Lin, Jungang Yang, Wei An
Based on our PAM, we propose a parallax-attention stereo matching network (PASMnet) and a parallax-attention stereo image super-resolution network (PASSRnet) for stereo matching and stereo image super-resolution tasks.
1 code implementation • 7 Jul 2020 • Yingqian Wang, Jungang Yang, Longguang Wang, Xinyi Ying, Tianhao Wu, Wei An, Yulan Guo
In this paper, we propose a deformable convolution network (i. e., LF-DFnet) to handle the disparity problem for LF image SR.
1 code implementation • 5 Jul 2020 • Gaochang Wu, Yingqian Wang, Yebin Liu, Lu Fang, Tianyou Chai
In this paper, we propose a spatial-angular attention network to perceive correspondences in the light field non-locally, and reconstruction high angular resolution light field in an end-to-end manner.
1 code implementation • CVPR 2021 • Longguang Wang, Xiaoyu Dong, Yingqian Wang, Xinyi Ying, Zaiping Lin, Wei An, Yulan Guo
Specifically, we develop a Sparse Mask SR (SMSR) network to learn sparse masks to prune redundant computation.
2 code implementations • ICCV 2021 • Longguang Wang, Yingqian Wang, Zaiping Lin, Jungang Yang, Wei An, Yulan Guo
In this paper, we propose to learn a scale-arbitrary image SR network from scale-specific networks.
1 code implementation • 6 Apr 2020 • Xinyi Ying, Longguang Wang, Yingqian Wang, Weidong Sheng, Wei An, Yulan Guo
In this paper, we propose a deformable 3D convolution network (D3Dnet) to incorporate spatio-temporal information from both spatial and temporal dimensions for video SR.
1 code implementation • 17 Dec 2019 • Yingqian Wang, Longguang Wang, Jungang Yang, Wei An, Jingyi Yu, Yulan Guo
Specifically, spatial and angular features are first separately extracted from input LFs, and then repetitively interacted to progressively incorporate spatial and angular information.
1 code implementation • 10 Dec 2019 • Yingqian Wang, Tianhao Wu, Jungang Yang, Longguang Wang, Wei An, Yulan Guo
In this paper, we handle the LF de-occlusion (LF-DeOcc) problem using a deep encoder-decoder network (namely, DeOccNet).
no code implementations • 15 Mar 2019 • Yingqian Wang, Longguang Wang, Jungang Yang, Wei An, Yulan Guo
With the popularity of dual cameras in recently released smart phones, a growing number of super-resolution (SR) methods have been proposed to enhance the resolution of stereo image pairs.
1 code implementation • CVPR 2019 • Longguang Wang, Yingqian Wang, Zhengfa Liang, Zaiping Lin, Jungang Yang, Wei An, Yulan Guo
Stereo image pairs can be used to improve the performance of super-resolution (SR) since additional information is provided from a second viewpoint.
Ranked #1 on Image Super-Resolution on KITTI 2012 - 4x upscaling