12 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding
Yi-Xing Peng, Qize Yang, Yu-Ming Tang +4
Fine-grained understanding of human actions and poses in videos is essential for human-centric AI applications. In this work, we introduce ActionArt, a fine-grained video-caption d…
Modeling Multiple Normal Action Representations for Error Detection in Procedural Tasks
Wei-Jin Huang, Yuan-Ming Li, Zhi-Wei Xia +4
Error detection in procedural activities is essential for consistent and correct outcomes in AR-assisted and robotic systems. Existing methods often focus on temporal ordering erro…
ChainHOI: Joint-based Kinematic Chain Modeling for Human-Object Interaction Generation
Ling-An Zeng, Guohong Huang, Yi-Lin Wei +4
We propose ChainHOI, a novel approach for text-driven human-object interaction (HOI) generation that explicitly models interactions at both the joint and kinetic chain levels. Unli…
iManip: Skill-Incremental Learning for Robotic Manipulation
Zexin Zheng, Jia-Feng Cai, Xiao-Ming Wu +3
The development of a generalist agent with adaptive multiple manipulation skills has been a long-standing goal in the robotics community. In this paper, we explore a crucial task,…
MaintaAvatar: A Maintainable Avatar Based on Neural Radiance Fields by Continual Learning
Shengbo Gu, Yu-Kun Qiu, Yu-Ming Tang +2
The generation of a virtual digital avatar is a crucial research topic in the field of computer vision. Many existing works utilize Neural Radiance Fields (NeRF) to address this is…