High-Fidelity Relightable Monocular Portrait Animation with Lighting-Controllable Video Diffusion Model
Mingtao Guo, Guanyu Xing, Yanli Liu
2025Year
3Top-tier citations
Abstract
Relightable portrait animation aims to animate a static reference portrait to match the head movements of a driving video while adapting to user-specified or reference lighting conditions. Existing portrait animation methods fail to achieve relightable portraits because they do not separate and manipulate intrinsic (identity and appearance)
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Cited by top-tier papers3
- PersonaLive! Expressive Portrait Image Animation for Live StreamingZhiyuan Li, Chi-Man Pun, Chen Fang, Jue Wang et al.CVPR 2026 · 6 citations
- PerformRecast: Expression and Head Pose Disentanglement for Portrait Video EditingJiadong Liang, Bojun Xiong, Jie Tian, Hua Li et al.CVPR 2026
- Relightful Video Portrait HarmonizationJun Myeong Choi, Jae Shin Yoon, Luchao Qi, Roni Sengupta et al.CVPR 2026
Builds on35
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 11,743 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
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