no code implementations • 8 Nov 2021 • Handong Ma, Changsheng Li, Xinchu Shi, Ye Yuan, Guoren Wang
To make the learnt graph structure more stable and effective, we take into account $k$-nearest neighbor graph as a priori, and learn a relation propagation graph structure.
no code implementations • 10 May 2021 • Xiao-Yu Zhang, Haichao Shi, Changsheng Li, Xinchu Shi
Weakly supervised action localization is a challenging task with extensive applications, which aims to identify actions and the corresponding temporal intervals with only video-level annotations available.
no code implementations • CVPR 2016 • Xinchu Shi, Haibin Ling, Weiming Hu, Junliang Xing, Yanning Zhang
Due to its wide range of applications, matching between two graphs has been extensively studied and remains an active topic.
no code implementations • CVPR 2014 • Xinchu Shi, Haibin Ling, Weiming Hu, Chunfeng Yuan, Junliang Xing
In this paper, we model interactions between neighbor targets by pair-wise motion context, and further encode such context into the global association optimization.
no code implementations • CVPR 2013 • Xinchu Shi, Haibin Ling, Junling Xing, Weiming Hu
In this paper we formulate multi-target tracking (MTT) as a rank-1 tensor approximation problem and propose an 1 norm tensor power iteration solution.