activity
20242026
most citedInterAct: A Large-Scale Dataset of Dynamic, Expressive and Interactive Activities between Two People in Daily Scenarios

1 citations · 1 across the 9 of their papers we have counts for

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cs.CV2026

MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation

Yifei Zhu, Mingyi Shi, Yangyang Cai +3

Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to first project motion data into…

cs.CV2026

LPM 1.0: Video-based Character Performance Model

Ailing Zeng, Casper Yang, Chauncey Ge +22

Performance, the externalization of intent, emotion, and personality through visual, vocal, and temporal behavior, is what makes a character alive. Learning such performance from v…

cs.CV2025

OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation

Guowei Xu, Yuxuan Bian, Ailing Zeng +6

This paper introduces OmniMotion-X, a versatile multimodal framework for whole-body human motion generation, leveraging an autoregressive diffusion transformer in a unified sequenc…

cs.CV20251 cited

InterAct: A Large-Scale Dataset of Dynamic, Expressive and Interactive Activities between Two People in Daily Scenarios

Leo Ho, Yinghao Huang, Dafei Qin +5

We address the problem of accurate capture of interactive behaviors between two people in daily scenarios. Most previous works either only consider one person or solely focus on co…

cs.CV2024

InterAct: Capture and Modelling of Realistic, Expressive and Interactive Activities between Two Persons in Daily Scenarios

Yinghao Huang, Leo Ho, Dafei Qin +2

We address the problem of accurate capture and expressive modelling of interactive behaviors happening between two persons in daily scenarios. Different from previous works which e…