This is a simplified guide to an AI model called Video-Retalking maintained by Cjwbw. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model overview
video-retalking is a system developed by researchers at Tencent AI Lab and Xidian University that enables audio-based lip synchronization and expression editing for talking head videos. It builds on prior work like Wav2Lip, PIRenderer, and GFP-GAN to create a pipeline for generating high-quality, lip-synced videos from talking head footage and audio. Unlike models like voicecraft, which focus on speech editing, or tokenflow, which aims for consistent video editing, video-retalking is specifically designed for synchronizing lip movements with audio.
Model inputs and outputs
video-retalking takes two main inputs: a talking head video and an audio file. The model then generates a new video with the facial expressions and lip movements synchronized to the provided audio. This allows users to edit the appearance and emotion of a talking head video while preserving the original audio.
Inputs
- Face: Input video file of a talking-head.
- Input Audio: Input audio file to synchronize with the video.
Outputs
- Output: The generated video with synchronized lip movements and expressions.
Capabilities
video-retalking can generate high-qu...
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