PhysAnimator: Physics-Guided Generative Cartoon Animation
Tianyi Xie, Yiwei Zhao, Ying Jiang, Chenfanfu Jiang
2025年份
11顶会引用
摘要
Force Rig Figure 1 . PhysAnimator is a novel framework that combines physics principles with video diffusion models to generate high-quality animations from static anime illustrations, allowing users to specify external forces or rigging points for custom effects.
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引用它的顶会 Paper11
- 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
- PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video GenerationChen Wang, Chuhao Chen, Yiming Huang, Zhiyang Dou 等NeurIPS 2025 · 被引用 50 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
- MoAlign: Motion-Centric Representation Alignment for Video Diffusion ModelsAritra Bhowmik, Denis Korzhenkov, Cees G. M. Snoek, Amir Habibian 等ICLR 2026 · 被引用 15 次
- ProPhy: Progressive Physical Alignment for Dynamic World SimulationZijun Wang, Panwen Hu, Jing Wang, Terry Jingchen Zhang 等CVPR 2026 · 被引用 14 次
它引用的顶会 Paper32
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 被引用 6,759 次
- Video Diffusion ModelsJonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan 等NeurIPS 2022 · 被引用 2,948 次
- LRM: Large Reconstruction Model for Single Image to 3DYicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi 等ICLR 2024 · 被引用 813 次
- Structure and Content-Guided Video Synthesis with Diffusion ModelsPatrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog 等ICCV 2023 · 被引用 733 次
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