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Congsheng Xu

dblp:365/8534 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2025
0009-0007-2619-8827ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
3D vision · 78% Face, body and person analysis · 22%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › 3d scene understanding › object relation reasoning
human-object interaction
1.622025
Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions · ICCV 2025
HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objects · ECCV (4) 2024
Interaction techniques and input › spatial interaction
egocentric interaction
0.912025
Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions · ICCV 2025
Computer vision › 3D vision › motion capture
human motion capture
0.212024
Inter-X: Towards Versatile Human-Human Interaction Analysis · CVPR 2024

Methods — techniques the papers use, named apart from their topics

dataset · 1.7benchmark · 1.7
YearPublicationVenuePosition
2025 Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions
Liang Xu 0012, Chengqun Yang, Zili Lin, Fei Xu 0008, Congsheng Xu, Yiyi Zhang 0002, Jie Qin 0004, Xingdong Sheng, Yunhui Liu 0006, Xin Jin 0014, Yichao Yan, Wenjun Zeng 0001, Xiaokang Yang 0001
ICCV6
2024 Inter-X: Towards Versatile Human-Human Interaction Analysis
abstract
The analysis of the ubiquitous human-human interactions is pivotal for understanding humans as social beings. Existing human-human interaction datasets typically suffer from inaccurate body motions, lack of hand gestures and fine- grained textual descriptions. To better perceive and generate human-human interactions, we propose Inter-X, a currently largest human-human interaction dataset with accurate body movements and diverse interaction patterns, together with detailed hand gestures. The dataset includes
Liang Xu 0012, Xintao Lv, Yichao Yan, Xin Jin 0014, Shuwen Wu, Congsheng Xu, Yizhou Zhou, Fengyun Rao, Xingdong Sheng, Yunhui Liu 0006, Wenjun Zeng 0001, Xiaokang Yang 0001
CVPR6
2024 HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objects
Xintao Lv, Liang Xu 0012, Yichao Yan, Xin Jin 0014, Congsheng Xu, Shuwen Wu, Lincheng Li, Mengxiao Bi, Wenjun Zeng 0001, Xiaokang Yang 0001
ECCV (4)5