1 code implementation • ECCV 2020 • Zhenzhi Wang, Ziteng Gao, Li-Min Wang, Zhifeng Li, Gangshan Wu
To address these problems, we present a new boundary-aware cascade network by introducing two novel components.
Ranked #14 on Action Segmentation on GTEA
1 code implementation • 27 Nov 2023 • Zhenzhi Wang, Jingbo Wang, Yixuan Li, Dahua Lin, Bo Dai
Furthermore, we demonstrate that the distance between joint pairs for human-wise interactions can be generated using an off-the-shelf Large Language Model (LLM).
no code implementations • ICCV 2023 • Yixuan Li, Lihan Jiang, Linning Xu, Yuanbo Xiangli, Zhenzhi Wang, Dahua Lin, Bo Dai
While most of recent neural rendering works focus on objects and small-scale scenes, developing neural rendering methods for city-scale scenes is of great potential in many real-world applications.
no code implementations • 16 Sep 2021 • Zhenzhi Wang, Liyu Wu, Zhimin Li, Jiangfeng Xiong, Qinglin Lu
Our challenge includes two tasks: video structuring in the temporal dimension and multi-modal video classification.
2 code implementations • 10 Sep 2021 • Zhenzhi Wang, LiMin Wang, Tao Wu, TianHao Li, Gangshan Wu
Instead, from a perspective on temporal grounding as a metric-learning problem, we present a Mutual Matching Network (MMN), to directly model the similarity between language queries and video moments in a joint embedding space.
Ranked #3 on Temporal Sentence Grounding on Charades-STA
1 code implementation • ICCV 2021 • Yixuan Li, Lei Chen, Runyu He, Zhenzhi Wang, Gangshan Wu, LiMin Wang
Spatio-temporal action detection is an important and challenging problem in video understanding.