7 papers · 1 filter
UniMoFlow: Grounding Instruction-Driven 3D Human Motion Editing in Generation
Yilei Hua, Beibei Jing, Ce Zheng +3
Instruction-driven editing of 3D human motion requires precise spatiotemporal localization, rich semantic grounding, and strict preservation of unmodified content. Existing methods…
When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation
Siwei Meng, Yawei Luo, Shu Zhang +1
Text-to-video (T2V) generation models have achieved strong visual realism, but improving physical plausibility can come at the cost of semantic consistency with the input text. Thi…
Alignment Is All You Need For X-to-4D Generation
Qiaowei Miao, Kehan Li, Yawei Luo +1
Generative diffusion models excel at synthesizing high-quality images, videos, and 3D content under multimodal control. However, arbitrary user-defined modality-to-4D (X-to-4D) gen…
SARe: Structure-Aware Generative 3D Fragment Reassembly
Hanze Jia, Chunshi Wang, Yuxiao Yang +4
3D fragment reassembly estimates the rigid pose of each fragment to recover a complete object from unordered point clouds or meshes. The task becomes increasingly challenging as th…
PhyMAGIC: Physical Motion-Aware Generative Inference with Confidence-guided LLM
Siwei Meng, Yawei Luo, Ping Liu
Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. However, state-of-the-art video diffus…
Advances in 4D Generation: A Survey
Qiaowei Miao, Kehan Li, Jinsheng Quan +6
Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of…