5 papers
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…
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…
Closed-Form Concept Erasure via Double Projections
Chi Zhang, Jingpu Cheng, Zhixian Wang +1
While modern generative models such as diffusion-based architectures have enabled impressive creative capabilities, they also raise important safety and ethical risks. These concer…
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…
Grounding Creativity in Physics: A Brief Survey of Physical Priors in AIGC
Siwei Meng, Yawei Luo, Ping Liu
Recent advancements in AI-generated content have significantly improved the realism of 3D and 4D generation. However, most existing methods prioritize appearance consistency while…