1 code implementation • ICCV 2023 • Binglu Wang, Lei Zhang, Zhaozhong Wang, Yongqiang Zhao, Tianfei Zhou
This paper presents CORE, a conceptually simple, effective and communication-efficient model for multi-agent cooperative perception.
1 code implementation • 3 May 2023 • James Liang, Tianfei Zhou, Dongfang Liu, Wenguan Wang
We present CLUSTSEG, a general, transformer-based framework that tackles different image segmentation tasks (i. e., superpixel, semantic, instance, and panoptic) through a unified neural clustering scheme.
no code implementations • CVPR 2023 • Fang Zhao, Zekun Li, Shaoli Huang, Junwu Weng, Tianfei Zhou, Guo-Sen Xie, Jue Wang, Ying Shan
Once the anchor transformations are found, per-vertex nonlinear displacements of the garment template can be regressed in a canonical space, which reduces the complexity of deformation space learning.
1 code implementation • CVPR 2023 • Liulei Li, Wenguan Wang, Tianfei Zhou, Jianwu Li, Yi Yang
The objective of this paper is self-supervised learning of video object segmentation.
1 code implementation • 30 Jan 2023 • Tianfei Zhou, Ender Konukoglu
To reach this goal, we propose FedFA to tackle federated learning from a distinct perspective of federated feature augmentation.
no code implementations • 28 Nov 2022 • Jakob Geusen, Gustav Bredell, Tianfei Zhou, Ender Konukoglu
Partitioning an image into superpixels based on the similarity of pixels with respect to features such as colour or spatial location can significantly reduce data complexity and improve subsequent image processing tasks.
1 code implementation • 15 Sep 2022 • Wenguan Wang, Cheng Han, Tianfei Zhou, Dongfang Liu
We devise deep nearest centroids (DNC), a conceptually elegant yet surprisingly effective network for large-scale visual recognition, by revisiting Nearest Centroids, one of the most classic and simple classifiers.
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.
1 code implementation • 27 Mar 2022 • Liulei Li, Tianfei Zhou, Wenguan Wang, Lu Yang, Jianwu Li, Yi Yang
Our target is to learn visual correspondence from unlabeled videos.
3 code implementations • CVPR 2022 • Liulei Li, Tianfei Zhou, Wenguan Wang, Jianwu Li, Yi Yang
In this paper, we instead address hierarchical semantic segmentation (HSS), which aims at structured, pixel-wise description of visual observation in terms of a class hierarchy.
1 code implementation • CVPR 2022 • Chen Liang, Wenguan Wang, Tianfei Zhou, Yi Yang
In this paper, we propose a new task and dataset, Visual Abductive Reasoning (VAR), for examining abductive reasoning ability of machine intelligence in everyday visual situations.
1 code implementation • 18 Mar 2022 • Chen Liang, Wenguan Wang, Tianfei Zhou, Jiaxu Miao, Yawei Luo, Yi Yang
We explore the task of language-guided video segmentation (LVS).
Ranked #7 on Referring Expression Segmentation on A2D Sentences
Referring Expression Segmentation Referring Video Object Segmentation +5
1 code implementation • CVPR 2022 • Tianfei Zhou, Meijie Zhang, Fang Zhao, Jianwu Li
Particularly, we propose i) semantic contrast to drive network learning by contrasting massive categorical object regions, leading to a more holistic object pattern understanding, and ii) semantic aggregation to gather diverse relational contexts in the memory to enrich semantic representations.
1 code implementation • 2 Jan 2022 • Shunzhou Wang, Tianfei Zhou, Yao Lu, Huijun Di
DPT consists of two branches, with each associated with a Transformer for learning from an original or gradient image sequence.
no code implementations • CVPR 2022 • Liulei Li, Tianfei Zhou, Wenguan Wang, Lu Yang, Jianwu Li, Yi Yang
Our target is to learn visual correspondence from unlabeled videos.
1 code implementation • journal 2021 • Tianfei Zhou, Liulei Li, Xueyi Li, Chun-Mei Feng, Jianwu Li, Ling Shao
The framework explicitly encodes semantic dependencies in a group of images to discover rich semantic context for estimating more reliable pseudo ground-truths, which are subsequently employed to train more effective segmentation models.
2 code implementations • 15 Oct 2021 • Chun-Mei Feng, Huazhu Fu, Tianfei Zhou, Yong Xu, Ling Shao, David Zhang
Magnetic resonance (MR) imaging produces detailed images of organs and tissues with better contrast, but it suffers from a long acquisition time, which makes the image quality vulnerable to say motion artifacts.
1 code implementation • 2 Jul 2021 • Tianfei Zhou, Fatih Porikli, David Crandall, Luc van Gool, Wenguan Wang
Video segmentation -- partitioning video frames into multiple segments or objects -- plays a critical role in a broad range of practical applications, from enhancing visual effects in movie, to understanding scenes in autonomous driving, to creating virtual background in video conferencing.
1 code implementation • 20 Jun 2021 • Tianfei Zhou, Liulei Li, Gustav Bredell, Jianwu Li, Ender Konukoglu
The proposed network has two appealing characteristics: 1) The memory-augmented network offers the ability to quickly encode past segmentation information, which will be retrieved for the segmentation of other slices; 2) The quality assessment module enables the model to directly estimate the qualities of segmentation predictions, which allows an active learning paradigm where users preferentially label the lowest-quality slice for multi-round refinement.
no code implementations • 2 Jun 2021 • Chen Liang, Yu Wu, Tianfei Zhou, Wenguan Wang, Zongxin Yang, Yunchao Wei, Yi Yang
Referring video object segmentation (RVOS) aims to segment video objects with the guidance of natural language reference.
no code implementations • CVPR 2021 • Tianfei Zhou, Jianwu Li, Xueyi Li, Ling Shao
To address this, we introduce a novel approach for more accurate and efficient spatio-temporal segmentation.
1 code implementation • CVPR 2021 • Tianfei Zhou, Wenguan Wang, Zhiyuan Liang, Jianbing Shen
On existing public benchmarks, face forgery detection techniques have achieved great success.
1 code implementation • CVPR 2021 • Tianfei Zhou, Wenguan Wang, Si Liu, Yi Yang, Luc van Gool
To address the challenging task of instance-aware human part parsing, a new bottom-up regime is proposed to learn category-level human semantic segmentation as well as multi-person pose estimation in a joint and end-to-end manner.
no code implementations • 26 Feb 2021 • Yi Zhou, Lei Huang, Tianfei Zhou, Ling Shao
For chest X-ray imaging, annotating large-scale data requires professional domain knowledge and is time-consuming.
5 code implementations • ICCV 2021 • Wenguan Wang, Tianfei Zhou, Fisher Yu, Jifeng Dai, Ender Konukoglu, Luc van Gool
Inspired by the recent advance in unsupervised contrastive representation learning, we propose a pixel-wise contrastive framework for semantic segmentation in the fully supervised setting.
1 code implementation • 9 Dec 2020 • Xueyi Li, Tianfei Zhou, Jianwu Li, Yi Zhou, Zhaoxiang Zhang
We formulate WSSS as a novel group-wise learning task that explicitly models semantic dependencies in a group of images to estimate more reliable pseudo ground-truths, which can be used for training more accurate segmentation models.
Ranked #37 on Weakly-Supervised Semantic Segmentation on COCO 2014 val (using extra training data)
1 code implementation • ECCV 2020 • Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc van Gool, Dengxin Dai
This work proposes a weakly supervised approach for 3D object detection, only requiring a small set of weakly annotated scenes, associated with a few precisely labeled object instances.
1 code implementation • ECCV 2020 • Xiankai Lu, Wenguan Wang, Martin Danelljan, Tianfei Zhou, Jianbing Shen, Luc van Gool
How to make a segmentation model efficiently adapt to a specific video and to online target appearance variations are fundamentally crucial issues in the field of video object segmentation.
1 code implementation • 9 Mar 2020 • Tianfei Zhou, Shunzhou Wang, Yi Zhou, Yazhou Yao, Jianwu Li, Ling Shao
In this paper, we present a novel Motion-Attentive Transition Network (MATNet) for zero-shot video object segmentation, which provides a new way of leveraging motion information to reinforce spatio-temporal object representation.
Ranked #9 on Unsupervised Video Object Segmentation on FBMS test
1 code implementation • CVPR 2020 • Tianfei Zhou, Wenguan Wang, Siyuan Qi, Haibin Ling, Jianbing Shen
The interaction recognition network has two crucial parts: a relation ranking module for high-quality HOI proposal selection and a triple-stream classifier for relation prediction.
no code implementations • 19 Jan 2015 • Jinwu Liu, Yao Lu, Tianfei Zhou
Multiple Instance Learning (MIL) recently provides an appealing way to alleviate the drifting problem in visual tracking.
no code implementations • 28 Oct 2014 • Tianfei Zhou, Yao Lu, Feng Lv, Huijun Di, Qingjie Zhao, Jian Zhang
Stochastic sampling based trackers have shown good performance for abrupt motion tracking so that they have gained popularity in recent years.