HunyuanPortrait - A portrait animation generation framework jointly developed by Tencent Hunyuan and Tsinghua University, among other institutions.
HunyuanPortrait is a diffusion-based framework developed by Tencent's Hunyuan team in collaboration with Tsinghua University, Sun Yat-sen University, and Hong Kong University of Science and Technology. It's used to generate highly controllable and realistic portrait animations. Based on...
What is HunyuanPortrait?
HunyuanPortrait is a diffusion-based framework developed by Tencent's Hunyuan team in collaboration with Tsinghua University, Sun Yat-sen University, and Hong Kong University of Science and Technology. It's used to generate highly controllable and realistic portrait animations. Based on a given portrait image as an appearance reference and a video clip as a driving template, it animates the person in the reference image according to facial expressions and head poses in the driving video. HunyuanPortrait outperforms existing methods in terms of temporal consistency and controllability, exhibits strong generalization performance, and effectively decouples appearance and motion under different image styles. It is widely used in virtual reality, games, and human-computer interaction.
HunyuanPortrait's main functions
- Highly controllable portrait animation generationBased on a single portrait image as an appearance reference and a video clip as a driving template, the facial expressions and head postures in the driving video are accurately transferred to the reference portrait to generate natural and smooth animations.
- Strong identity consistencyIn cases where there are significant differences in facial structure and movement intensity, the identity characteristics of the reference portrait should be maintained to avoid identity distortion.
- Realistic facial motion captureIt captures subtle changes in facial expressions, such as eye direction and lip synchronization, to generate highly realistic portrait animations.
- Time consistency optimizationThe generated video has a high degree of temporal continuity and smoothness, avoiding problems such as background jitter and blur.
- Style generalization abilityIt adapts to different image styles, including anime and realistic photo styles, and has wide applicability.
The technical principles of HunyuanPortrait
- Implicit condition controlImplicit representation encoding of motion information allows for better capture of complex facial movements and expression changes, avoiding artifacts and distortions caused by inaccurate keypoint extraction. The encoded motion information is then used as a control signal and injected into the denoising U-Net based on an attention mechanism, enabling fine-grained control over the animation generation process.
- Stable video diffusion modelBased on a diffusion model framework, diffusion and denoising processes are performed in the latent space to improve generation quality and training efficiency. Images are mapped from RGB space to the latent space using VAE, and denoising is performed based on UNet to generate high-quality video frames.
- Enhanced Feature ExtractorThis approach enhances the representation of motion features based on estimated motion intensity (such as the degree of facial expression distortion and the amplitude of head movements), improving adaptability to different motion intensities. By combining ArcFace and DiNOv2 backgrounds, a multi-scale adapter (IMAdapter) is used to enhance the identity consistency of portraits, ensuring that the generated animation maintains consistent identity features across different frames.
- Training and reasoning strategiesTechniques such as color jitter and pose guidance are used to enhance the diversity of training data and improve the model's generalization ability. Various training enhancement strategies, such as randomly removing certain bone edges, are employed to improve the model's stability under different input conditions.
- Attention mechanismIntroducing multi-head self-attention and cross-attention mechanisms into UNet enhances the model's ability to perceive spatial and temporal information, thereby improving the detail richness and temporal consistency of the generated videos.
HunyuanPortrait's project address
- Project official website:https://kkakkkka.github.io/HunyuanPortrait/
- GitHub repository:https://github.com/Tencent-Hunyuan/HunyuanPortrait
- HuggingFace model library:https://huggingface.co/tencent/HunyuanPortrait
- arXiv technical paper:https://arxiv.org/pdf/2503.18860
Application scenarios of HunyuanPortrait
- Virtual Reality (VR) and Augmented Reality (AR)Create realistic virtual characters to enhance the user experience.
- Game developmentGenerate personalized game characters to enhance player immersion.
- Human-computer interactionDevelop more natural virtual assistants and customer service robots to enhance the interactive experience.
- Digital content creationUsed in video production, advertising, and film and television special effects to quickly generate high-quality animated content.
- Social media and entertainmentUsers can create animated emoticons or virtual avatars from their own photos to increase interactivity.
- Education and trainingCreate personalized virtual teacher or training roles to provide a more engaging teaching experience.