activity
20202026
most citedProposal Relation Network for Temporal Action Detection

16 citations · 91 across the 14 of their papers we have counts for

collaborators

15 papers

cs.CV2026

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

Yujie Wei, Yujin Han, Zhekai Chen +20

Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However, evaluating such frontier mo…

cs.CV202212 cited

Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning

Yixuan Pei, Zhiwu Qing, Jun Cen +6

Recent incremental learning for action recognition usually stores representative videos to mitigate catastrophic forgetting. However, only a few bulky videos can be stored due to t…

cs.CV20227 cited

Hybrid Relation Guided Set Matching for Few-shot Action Recognition

Xiang Wang, Shiwei Zhang, Zhiwu Qing +5

Current few-shot action recognition methods reach impressive performance by learning discriminative features for each video via episodic training and designing various temporal ali…

cs.CV2022

Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency

Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +6

Natural videos provide rich visual contents for self-supervised learning. Yet most existing approaches for learning spatio-temporal representations rely on manually trimmed videos,…

cs.CV20213 cited

Exploring Stronger Feature for Temporal Action Localization

Zhiwu Qing, Xiang Wang, Ziyuan Huang +6

Temporal action localization aims to localize starting and ending time with action category. Limited by GPU memory, mainstream methods pre-extract features for each video. Therefor…

cs.CV20211 cited

OadTR: Online Action Detection with Transformers

Xiang Wang, Shiwei Zhang, Zhiwu Qing +4

Most recent approaches for online action detection tend to apply Recurrent Neural Network (RNN) to capture long-range temporal structure. However, RNN suffers from non-parallelism…