Ammmob/PixelSmile
PixelSmile: Fine-grained facial expression editing with continuous control, reduced semantic entanglement, and strong identity preservation.
What it solves
PixelSmile enables fine-grained editing of facial expressions in images, allowing users to change the emotion of a person (or anime character) while maintaining their identity and the overall image context.
How it works
It builds upon the Qwen-Image-Edit-2511 base model, using a LoRA (Low-Rank Adaptation) approach to specialize the model for expression editing. During training, it utilizes CLIP encoders for text/image understanding and InsightFace (ArcFace) to ensure identity embeddings are preserved, preventing the person's face from changing into someone else during the edit.
Who it’s for
- AI researchers and developers working on image manipulation and facial analysis.
- Digital artists and creators who need precise control over facial expressions in generated or existing images.
- Users of ComfyUI looking for advanced conditioning interpolation for facial edits.
Highlights
- Fine-grained control: Specifically designed for precise facial expression modifications.
- Identity preservation: Uses identity embeddings to keep the subject recognizable.
- Multi-domain support: Supports both human and anime facial expressions.
- Flexible deployment: Provides inference code, training scripts, and community support for ComfyUI.