1 code implementation • 28 Mar 2024 • Xiao Lin, Wenfei Yang, Yuan Gao, Tianzhu Zhang
(2) The second design is a Geometric-Aware Feature Aggregation module, which can efficiently integrate the local and global geometric information into keypoint features.
no code implementations • 7 Mar 2024 • Yu Zhu, Chuxiong Sun, Wenfei Yang, Wenqiang Wei, Bo Tang, Tianzhu Zhang, Zhiyu Li, Shifeng Zhang, Feiyu Xiong, Jie Hu, MingChuan Yang
Reinforcement Learning from Human Feedback (RLHF) is the prevailing approach to ensure Large Language Models (LLMs) align with human values.
1 code implementation • 20 Jan 2024 • Yinchao Ma, Yuyang Tang, Wenfei Yang, Tianzhu Zhang, Jinpeng Zhang, Mengxue Kang
Single object tracking aims to locate the target object in a video sequence according to the state specified by different modal references, including the initial bounding box (BBOX), natural language (NL), or both (NL+BBOX).
no code implementations • 7 Jan 2024 • Xianghui Xie, Xi Wang, Nikos Athanasiou, Bharat Lal Bhatnagar, Chun-Hao P. Huang, Kaichun Mo, Hao Chen, Xia Jia, Zerui Zhang, Liangxian Cui, Xiao Lin, Bingqiao Qian, Jie Xiao, Wenfei Yang, Hyeongjin Nam, Daniel Sungho Jung, Kihoon Kim, Kyoung Mu Lee, Otmar Hilliges, Gerard Pons-Moll
Modeling the interaction between humans and objects has been an emerging research direction in recent years.
no code implementations • ICCV 2023 • Chuxin Wang, Wenfei Yang, Tianzhu Zhang
Semi-supervised 3D object detection from point cloud aims to train a detector with a small number of labeled data and a large number of unlabeled data.
1 code implementation • CVPR 2023 • Huan Ren, Wenfei Yang, Tianzhu Zhang, Yongdong Zhang
Weakly-supervised temporal action localization aims to localize and recognize actions in untrimmed videos with only video-level category labels during training.
Ranked #2 on Weakly Supervised Action Localization on THUMOS’14
Multiple Instance Learning Weakly Supervised Action Localization +2
no code implementations • CVPR 2021 • Wenfei Yang, Tianzhu Zhang, Xiaoyuan Yu, Tian Qi, Yongdong Zhang, Feng Wu
To alleviate this problem, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other.
no code implementations • CVPR 2021 • Wang Luo, Tianzhu Zhang, Wenfei Yang, Jingen Liu, Tao Mei, Feng Wu, Yongdong Zhang
In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.
Ranked #7 on Weakly Supervised Action Localization on THUMOS14
Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1