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Found 3 papers, 1 papers with code
Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video Grounding
In the weakly supervised temporal video grounding study, previous methods use predetermined single Gaussian proposals which lack the ability to express diverse events described by the sentence query.
Position-aware Location Regression Network for Temporal Video Grounding
The key to successful grounding for video surveillance is to understand a semantic phrase corresponding to important actors and objects.
Skeleton-based Action Recognition of People Handling Objects
In this paper, to address this problem, we propose a new framework for recognizing object-related human actions by graph convolutional networks using human and object poses.
Ranked #1 on
Action Recognition
on IRD
