3 papers
cs.CV2025
Spatiotemporal-Untrammelled Mixture of Experts for Multi-Person Motion Prediction
Zheng Yin, Chengjian Li, Xiangbo Shu +3
Comprehensively and flexibly capturing the complex spatio-temporal dependencies of human motion is critical for multi-person motion prediction. Existing methods grapple with two pr…
cs.CV2025
Plenodium: UnderWater 3D Scene Reconstruction with Plenoptic Medium Representation
Changguanng Wu, Jiangxin Dong, Chengjian Li +1
We present Plenodium (plenoptic medium), an effective and efficient 3D representation framework capable of jointly modeling both objects and participating media. In contrast to exi…
cs.CV2024
FTMoMamba: Motion Generation with Frequency and Text State Space Models
Chengjian Li, Xiangbo Shu, Qiongjie Cui +2
Diffusion models achieve impressive performance in human motion generation. However, current approaches typically ignore the significance of frequency-domain information in capturi…