most citedFineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding

31 citations · 64 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021★ 23 cited

Revisiting Skeleton-based Action Recognition

Haodong Duan, Yue Zhao, Kai Chen +2

Human skeleton, as a compact representation of human action, has received increasing attention in recent years. Many skeleton-based action recognition methods adopt graph convoluti…

cs.CV2020

DecAug: Augmenting HOI Detection via Decomposition

Yichen Xie, Hao-Shu Fang, Dian Shao +2

Human-object interaction (HOI) detection requires a large amount of annotated data. Current algorithms suffer from insufficient training samples and category imbalance within datas…

cs.CV2020★ 2 cited

DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection

Hao-Shu Fang, Yichen Xie, Dian Shao +1

Recent years, human-object interaction (HOI) detection has achieved impressive advances. However, conventional two-stage methods are usually slow in inference. On the other hand, e…

cs.CV2020★ 8 cited

Intra- and Inter-Action Understanding via Temporal Action Parsing

Dian Shao, Yue Zhao, Bo Dai +1

Current methods for action recognition primarily rely on deep convolutional networks to derive feature embeddings of visual and motion features. While these methods have demonstrat…

cs.CV2020★ 31 cited

FineGym: A Hierarchical Video Dataset for Fine-grained Action Understanding

Dian Shao, Yue Zhao, Bo Dai +1

On public benchmarks, current action recognition techniques have achieved great success. However, when used in real-world applications, e.g. sport analysis, which requires the capa…