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cs.CV2026
Inter-X++: A Comprehensive Benchmark for Multimodal Human-Human Interaction Analysis
Liang Xu, Chengqun Yang, Zili Lin +6
The capability to perceive and synthesize human-human interactions is fundamental to developing intelligent digital human systems. However, existing datasets and modeling approache…
cs.CV2025
Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions
Liang Xu, Chengqun Yang, Zili Lin +11
Learning action models from real-world human-centric interaction datasets is important towards building general-purpose intelligent assistants with efficiency. However, most existi…
cs.CV2024
MotionBank: A Large-scale Video Motion Benchmark with Disentangled Rule-based Annotations
Liang Xu, Shaoyang Hua, Zili Lin +6
In this paper, we tackle the problem of how to build and benchmark a large motion model (LMM). The ultimate goal of LMM is to serve as a foundation model for versatile motion-relat…