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…
CPT-Interp: Continuous sPatial and Temporal Motion Modeling for 4D Medical Image Interpolation
Xia Li, Runzhao Yang, Xiangtai Li +3
Motion information from 4D medical imaging offers critical insights into dynamic changes in patient anatomy for clinical assessments and radiotherapy planning and, thereby, enhance…
Continuous sPatial-Temporal Deformable Image Registration (CPT-DIR) for motion modelling in radiotherapy: beyond classic voxel-based methods
Xia Li, Runzhao Yang, Muheng Li +4
Deformable image registration (DIR) is a crucial tool in radiotherapy for analyzing anatomical changes and motion patterns. Current DIR implementations rely on discrete volumetric…
Skeleton-in-Context: Unified Skeleton Sequence Modeling with In-Context Learning
Xinshun Wang, Zhongbin Fang, Xia Li +2
In-context learning provides a new perspective for multi-task modeling for vision and NLP. Under this setting, the model can perceive tasks from prompts and accomplish them without…
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…