

Portraitgen
Overview :
PortraitGen is a multimodal generative prior-based tool for editing 2D portrait videos, capable of enhancing them to 4D Gaussian fields for multimodal portrait editing. The technology quickly generates and edits 3D portraits by tracking SMPL-X coefficients and utilizing a neural Gaussian texture mechanism. It also introduces an iterative dataset updating strategy and a multimodal face-aware editing module to improve expression quality while maintaining personalized facial structures.
Target Users :
Target audience includes video editors, animators, and game developers who require the editing and creation of portrait videos. PortraitGen offers a fast, efficient, and multimodal editing approach, particularly suitable for users who need to complete high-quality portrait video editing within a short time frame.
Use Cases
Video editors use PortraitGen to quickly generate personalized portrait videos.
Game developers utilize PortraitGen to create diverse expressions and movements for game characters.
Animators use PortraitGen for character design and animation production.
Features
Multimodal portrait editing: Utilizing InstructPix2Pix as a 2D editing model to achieve text-driven and image-driven editing.
Style transfer: Applying neural style transfer algorithms to transfer the style of reference images onto dataset frames.
Virtual fitting: Using AnyDoor technology to change the clothing of the subject.
Relighting: Adjusting the lighting conditions of video frames based on text descriptions using IC-Light technology.
Expression similarity guidance: Optimizing by EMOCA's latent expression space to maintain natural and consistent expressions.
Face-aware portrait editing: Enhancing awareness of facial structure and improving editing robustness through two iterations.
Iterative dataset updating strategy: Enhancing editing performance through iterative dataset updates.
How to Use
1. Visit the PortraitGen website.
2. Choose the editing mode: text-driven editing, image-driven editing, or relighting.
3. Upload the 2D portrait video you want to edit.
4. Enter text instructions or select reference images to perform style transfer or virtual fitting as needed.
5. Adjust lighting conditions if necessary.
6. Conduct face-aware portrait editing to ensure the accuracy of facial structure.
7. Optimize editing results through an iterative dataset updating strategy.
8. Preview the edited 3D portrait video.
9. Export the completed video.
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