2 code implementations • 1 Aug 2023 • Mingzhan Yang, Guangxin Han, Bin Yan, Wenhua Zhang, Jinqing Qi, Huchuan Lu, Dong Wang
Also, our method shows strong generalization for diverse trackers and scenarios in a plug-and-play and training-free manner.
Ranked #5 on Multi-Object Tracking on DanceTrack
no code implementations • 3 Oct 2022 • Hongsheng Wang, Xiaoqi Zhao, Youwei Pang, Jinqing Qi
In this research, we propose a rich prototype generation module (RPGM) and a recurrent prediction enhancement module (RPEM) to reinforce the prototype learning paradigm and build a unified memory-augmented decoder for few-shot segmentation, respectively.
1 code implementation • 13 Jul 2021 • Guowen Zhang, Pingping Zhang, Jinqing Qi, Huchuan Lu
In this work, we take advantages of both CNNs and Transformers, and propose a novel learning framework named Hierarchical Aggregation Transformer (HAT) for image-based person Re-ID with high performance.
1 code implementation • ICCV 2021 • Shu Yang, Lu Zhang, Jinqing Qi, Huchuan Lu, Shuo Wang, Xiaoxing Zhang
How to make the appearance and motion information interact effectively to accommodate complex scenarios is a fundamental issue in flow-based zero-shot video object segmentation.
Semantic Segmentation Unsupervised Video Object Segmentation +2
no code implementations • 25 Oct 2020 • Mingyang Qian, Yi Fu, Xiao Tan, YingYing Li, Jinqing Qi, Huchuan Lu, Shilei Wen, Errui Ding
Video segmentation approaches are of great importance for numerous vision tasks especially in video manipulation for entertainment.
3 code implementations • 12 Sep 2018 • Yunhua Zhang, Dong Wang, Lijun Wang, Jinqing Qi, Huchuan Lu
Compared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if present or conducting image-wide re-detection if absent.
no code implementations • ECCV 2018 • Yunhua Zhang, Lijun Wang, Jinqing Qi, Dong Wang, Mengyang Feng, Huchuan Lu
In this paper, we circumvent this issue by proposing a local structure learning method, which simultaneously considers the local patterns of the target and their structural relationships for more accurate target tracking.
1 code implementation • CVPR 2018 • Xiaoning Zhang, Tiantian Wang, Jinqing Qi, Huchuan Lu, Gang Wang
In this paper, we propose a novel attention guided network which selectively integrates multi-level contextual information in a progressive manner.
Ranked #11 on RGB Salient Object Detection on DUTS-TE (max F-measure metric)