Diff2Lip vs MakeItTalk

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.

MakeItTalk is Linux, self-hosted software that creates expressive talking-head videos from one facial image and an audio track. Audio content drives lip movement and nearby facial motion, while speaker information influences expressions and other talking-head movement. The project describes use with human portraits, paintings, sketches, 2D cartoons, manga, and stylized caricatures, including faces or characters not seen during training. Its repository includes pretrained models, module training code, and Google Colab demos for natural faces. For human faces and paintings, the README calls for a centered 256×256 JPG portrait and a WAV file. Optional command-line settings adjust lip motion on the x and y axes and head-motion displacement. Local setup specifies Python 3.6, ffmpeg, and Python packages; cartoon face warping on Ubuntu also requires winehq-stable. Custom puppets are listed as a to-do item, and training sections for voice conversion, the speaker-aware branch, and image-to-image translation are marked unfinished. It is free open-source research code under CC BY-NC 4.0, allowing noncommercial use under that license.