no code implementations • 2 May 2024 • Peng Chu, Jiang Wang, Andre Abrantes
The development of Audio Description (AD) has been a pivotal step forward in making video content more accessible and inclusive.
no code implementations • 7 Jun 2023 • Andre Abrantes, Jiang Wang, Peng Chu, Quanzeng You, Zicheng Liu
We introduce a novel framework called RefineVIS for Video Instance Segmentation (VIS) that achieves good object association between frames and accurate segmentation masks by iteratively refining the representations using sequence context.
Ranked #5 on
Video Instance Segmentation
on YouTube-VIS 2021
(using extra training data)
no code implementations • 14 Jun 2022 • Quanzeng You, Jiang Wang, Peng Chu, Andre Abrantes, Zicheng Liu
We propose a consistent end-to-end video instance segmentation framework with Inter-Frame Recurrent Attention to model both the temporal instance consistency for adjacent frames and the global temporal context.
no code implementations • CVPR 2023 • Shiqi Lin, Zhizheng Zhang, Zhipeng Huang, Yan Lu, Cuiling Lan, Peng Chu, Quanzeng You, Jiang Wang, Zicheng Liu, Amey Parulkar, Viraj Navkal, Zhibo Chen
Improving the generalization ability of Deep Neural Networks (DNNs) is critical for their practical uses, which has been a longstanding challenge.
no code implementations • CVPR 2022 • Zhipeng Huang, Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Peng Chu, Quanzeng You, Jiang Wang, Zicheng Liu, Zheng-Jun Zha
In this paper, to address more practical scenarios, we propose a new task, Lifelong Unsupervised Domain Adaptive (LUDA) person ReID.
Domain Adaptive Person Re-Identification
Knowledge Distillation
+4
no code implementations • 30 Nov 2021 • Xiaotian Han, Quanzeng You, Chunyu Wang, Zhizheng Zhang, Peng Chu, Houdong Hu, Jiang Wang, Zicheng Liu
This dataset provides a more reliable benchmark of multi-camera, multi-object tracking systems in cluttered and crowded environments.
Ranked #2 on
Object Tracking
on MMPTRACK
no code implementations • 1 Apr 2021 • Peng Chu, Jiang Wang, Quanzeng You, Haibin Ling, Zicheng Liu
TransMOT effectively models the interactions of a large number of objects by arranging the trajectories of the tracked objects as a set of sparse weighted graphs, and constructing a spatial graph transformer encoder layer, a temporal transformer encoder layer, and a spatial graph transformer decoder layer based on the graphs.
Ranked #2 on
Multi-Object Tracking
on 2DMOT15
(using extra training data)
1 code implementation • CVPR 2021 • Hexin Bai, Wensheng Cheng, Peng Chu, Juehuan Liu, Kai Zhang, Haibin Ling
Multiple Object Tracking (MOT) has witnessed remarkable advances in recent years.
1 code implementation • 8 Sep 2020 • Heng Fan, Hexin Bai, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Harshit, Mingzhen Huang, Juehuan Liu, Yong Xu, Chunyuan Liao, Lin Yuan, Haibin Ling
The average video length of LaSOT is around 2, 500 frames, where each video contains various challenge factors that exist in real world video footage, such as the targets disappearing and re-appearing.
no code implementations • ECCV 2020 • Peng Chu, Xiao Bian, Shaopeng Liu, Haibin Ling
Real-world data often follow a long-tailed distribution as the frequency of each class is typically different.
Ranked #26 on
Long-tail Learning
on Places-LT
1 code implementation • 10 Jun 2020 • Ruining Deng, Haichun Yang, Aadarsh Jha, Yuzhe Lu, Peng Chu, Agnes B. Fogo, Yuankai Huo
However, the 3D identification and association of large-scale glomeruli on renal pathology is challenging due to large tissue deformation, missing tissues, and artifacts from WSI.
no code implementations • 27 May 2020 • Hexin Bai, Peng Chu, Jeng-Yuan Tsai, Nathan Wilson, Xiaofeng Qian, Qimin Yan, Haibin Ling
Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties.
no code implementations • 18 Nov 2019 • Heng Fan, Fan Yang, Peng Chu, Lin Yuan, Haibin Ling
For the analysis component, given the tracking results on all sequences, it investigates the behavior of the tracker under each individual factor and generates the report automatically.
1 code implementation • ICCV 2019 • Fan Yang, Heng Fan, Peng Chu, Erik Blasch, Haibin Ling
The key components in ClusDet include a cluster proposal sub-network (CPNet), a scale estimation sub-network (ScaleNet), and a dedicated detection network (DetecNet).
no code implementations • ICCV 2019 • Peng Chu, Haibin Ling
Data association-based multiple object tracking (MOT) involves multiple separated modules processed or optimized differently, which results in complex method design and requires non-trivial tuning of parameters.
no code implementations • 21 Feb 2019 • Peng Chu, Heng Fan, Chiu C. Tan, Haibin Ling
To address this issue, in this paper we propose an instance-aware tracker to integrate SOT techniques for MOT by encoding awareness both within and between target models.
no code implementations • 9 Nov 2018 • Heng Fan, Peng Chu, Longin Jan Latecki, Haibin Ling
Recurrent neural networks (RNNs) have shown the ability to improve scene parsing through capturing long-range dependencies among image units.
1 code implementation • CVPR 2019 • Heng Fan, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Hexin Bai, Yong Xu, Chunyuan Liao, Haibin Ling
In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking.