PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation
Qiyao Xue, Xiangyu Yin, Boyuan Yang, Wei Gao
2025年份
21顶会引用
摘要
Multiple apples, bouncing Single apple, no bouncing Drawing content disappears Drawing with causality No water splashing Water splashing Calm water Flooding river No tumbling rock Rock tumbling No tea filling and steam of hot tea Tea is filling the cup with steam Figure 1. Left: videos generated by the current text-to-video generation model (CogVideoX-5B [50] ) cannot adhere to the real-world physical rules (described in brackets following the user prompt). Right: our method PhyT2V, when applied to the same model, better reflects the real-world physical knowledge.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper21
- VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation ModelsXiangdong Zhang, Jiaqi Liao, Shaofeng Zhang, Fanqing Meng 等NeurIPS 2025 · 被引用 98 次
- WISA: World simulator assistant for physics-aware text-to-video generationJing Wang, Ao Ma, Ke Cao, Jun Zheng 等NeurIPS 2025 · 被引用 93 次
- Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and VisionLuozheng Qin, Jia Gong, Yuqing Sun, Tianjiao Li 等ICLR 2026 · 被引用 55 次
- NewtonGen: Physics-consistent and Controllable Text-to-Video Generation via Neural Newtonian DynamicsYu Yuan, Xijun Wang, Tharindu Wickremasinghe, Zeeshan Nadir 等ICLR 2026 · 被引用 46 次
- Inference-time Physics Alignment of Video Generative Models with Latent World ModelsJianhao Yuan, Xiaofeng Zhang, Felix Friedrich, Nicolas Beltran-Velez 等CVPR 2026 · 被引用 32 次
它引用的顶会 Paper18
- Scalable Diffusion Models with TransformersWilliam Peebles, Saining XieICCV 2023 · 被引用 5,568 次
- A Survey on In-context LearningQingxiu Dong, Lei Li, Damai Dai, Ce Zheng 等EMNLP 2024 · 被引用 479 次
- InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and GenerationYi Wang, Yinan He, Yizhuo Li, Kunchang Li 等ICLR 2024 · 被引用 467 次
- Make-A-Video: Text-to-Video Generation without Text-Video DataUriel Singer, Adam Polyak, Thomas Hayes, Xi Yin 等ICLR 2023 · 被引用 313 次
- Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMsLing Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu 等ICML 2024 · 被引用 231 次
相关 Paper
- VideoPhy: Evaluating Physical Commonsense for Video GenerationHritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong 等ICLR 2025 · 被引用 1 次
- Tora: Trajectory-oriented Diffusion Transformer for Video GenerationZhenghao Zhang, Junchao Liao, Menghao Li, Zuozhuo Dai 等CVPR 2025
- PhysGen3D: Crafting a Miniature Interactive World from a Single ImageBoyuan Chen, Hanxiao Jiang, Shaowei Liu, Saurabh Gupta 等CVPR 2025
- PhyWorldBench: A Comprehensive Evaluation of Physical Realism in Text-to-Video ModelsJing Gu, Xian Liu, Yu Zeng, Ashwin Nagarajan 等ICLR 2026 · 被引用 29 次
- Chain of Event-Centric Causal Thought for Physically Plausible Video GenerationZixuan Wang, Yixin Hu, Haolan Wang, Feng Chen 等CVPR 2026 · 被引用 8 次
