2 citations · 2 across the 4 of their papers we have counts for
5 papers
Human-in-Context: Unified Cross-Domain 3D Human Motion Modeling via In-Context Learning
Mengyuan Liu, Xinshun Wang, Zhongbin Fang +6
This paper aims to model 3D human motion across domains, where a single model is expected to handle multiple modalities, tasks, and datasets. Existing cross-domain models often rel…
VG4D: Vision-Language Model Goes 4D Video Recognition
Zhichao Deng, Xiangtai Li, Xia Li +3
Understanding the real world through point cloud video is a crucial aspect of robotics and autonomous driving systems. However, prevailing methods for 4D point cloud recognition ha…
Point-In-Context: Understanding Point Cloud via In-Context Learning
Mengyuan Liu, Zhongbin Fang, Xia Li +4
The rise of large-scale models has catalyzed in-context learning as a powerful approach for multitasking, particularly in natural language and image processing. However, its applic…
ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud Classification
Zhongbin Fang, Xia Li, Xiangtai Li +2
Recently, 3D point cloud classification has made significant progress with the help of many datasets. However, these datasets do not reflect the incomplete nature of real-world poi…
Explore Human Parsing Modality for Action Recognition
Jinfu Liu, Runwei Ding, Yuhang Wen +4
Multimodal-based action recognition methods have achieved high success using pose and RGB modality. However, skeletons sequences lack appearance depiction and RGB images suffer irr…