Upscaling / Super-Resolution

Many lip sync models operate at reduced resolutions internally for computational efficiency, generating mouth regions at lower resolution before compositing them back into the full-resolution video. Super-resolution networks upscale these lower-resolution outputs to match the original video quality, recovering fine details like skin pores, individual teeth edges, and lip texture.

This two-stage approach, generating at lower resolution then upscaling, enables faster inference while maintaining visual quality. Some lip sync systems also apply face-specific super-resolution to enhance the overall quality of the generated face region beyond what the base model produces.

Upscaling / Super-Resolution relates to several other concepts in the AI lip sync pipeline: Neural Rendering , and Resolution .