Diff2Lip vs VisualDub

Diff2Lip is a free, open-source Linux and self-hosted project that synchronizes speech with face videos using an audio-conditioned diffusion model. It accepts speech and face-video material and generates lip-synced video while aiming to preserve the identity shown in source frames. The repository includes inference scripts for audio-video pairs and for a single video. Cross mode drives a video with an audio source; reconstruction mode drives the video's first frame with audio. The project lists movies, education and virtual avatars as applications, with video conferencing described as a possible future use. Diff2Lip is not real time yet. Reported evaluations use the VoxCeleb2 and LRW datasets, and the repository identifies the work as a WACV 2024 paper. Setup instructions use Python 3.9, FFmpeg 5.0.1 and the requirements file. Inference supports one or more GPUs through NUM_GPUS, with values above one running distributed generation. A Google Colab notebook is linked for trying it.

VisualDub has no write-up on Specifiction yet; its figures are above.