1 code implementation • 6 Apr 2023 • Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu, Juan-Manuel Pérez-Rúa, Bernard Ghanem
To alleviate the boundary ambiguity, we propose to study the video activity localization problem from a denoising perspective.
Ranked #1 on Video Grounding on MAD
1 code implementation • 25 May 2022 • Xin Sun, Xuan Wang, Jialin Gao, Qiong Liu, Xi Zhou
Moment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description.
1 code implementation • EMNLP 2021 • Jialin Gao, Xin Sun, Mengmeng Xu, Xi Zhou, Bernard Ghanem
Temporal language grounding in videos aims to localize the temporal span relevant to the given query sentence.
no code implementations • 9 Mar 2020 • Jialin Gao, Zhixiang Shi, Jiani Li, Guanshuo Wang, Yufeng Yuan, Shiming Ge, Xi Zhou
Accurate temporal action proposals play an important role in detecting actions from untrimmed videos.
no code implementations • 24 Dec 2019 • Jialin Gao, Tong He, Xi Zhou, Shiming Ge
A collection of approaches based on graph convolutional networks have proven success in skeleton-based action recognition by exploring neighborhood information and dense dependencies between intra-frame joints.
Ranked #36 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • 28 Oct 2019 • Weiwei Zhang, Changsheng chen, Xuechun Wu, Jialin Gao, Di Bao, Jiwei Li, Xi Zhou
In this paper, we propose an adaptive pruning method.
no code implementations • 9 Aug 2019 • Jialin Gao, Zhixiang Shi, Jiani Li, Yufeng Yuan, Jiwei Li, Xi Zhou
In this technical report, we describe our solution to temporal action proposal (task 1) in ActivityNet Challenge 2019.