bytedance/LatentSync
LatentSync
LatentSync is an audio-driven video generator and latent diffusion lip sync model designed to synchronize a speaker's lip movements in a video to a target audio track. It provides a lip synchronization training framework for developing synchronization networks on custom video and audio datasets.
The system utilizes a video preprocessing pipeline to clean, segment, and align face data. It includes a visual sync evaluation tool that calculates confidence scores to measure the accuracy of audio and visual alignment in generated videos.
The project covers capabilities for custom synchronization network development, training configuration management for hardware memory and resolution, and synthetic video evaluation.
Features
- Latent Diffusion Models - Utilizes a latent diffusion model to generate synchronized video frames by denoising representations in a compressed space.
- Audio-Visual Semantic Alignment - Processes video and audio data to ensure facial movements match the timing and patterns of speech.
- Audio-Visual Conditioning - Implements conditioning that injects audio features and facial landmarks to guide the synthesis of synchronized lip movements.
- Latent Space Encoders - Performs computationally expensive synthesis within a compressed latent space before decoding to full resolution.
- Video Sequence Preprocessing - Provides utilities for cleaning and segmenting video files by aligning faces and filtering for visual quality.
- Face-Centric Video Cleaning - Cleans and segments video files by aligning faces and filtering for quality before training synchronization models.
- Facial Region Alignment - Aligns and crops video frames to focus on the mouth region for precise synchronization training.
- Lip Sync Model Training - Provides a framework for training neural networks on custom datasets to optimize audio-to-lip mapping.
- Lip Sync Models - Implements a generative AI model that synchronizes a speaker's lip movements in video to target audio using latent diffusion.
- Sync Accuracy Metrics - Implements a visual sync evaluation tool that calculates confidence scores to measure the accuracy of audio-visual alignment.
- Audio-Driven Talking Head Synthesis - Generates realistic facial animations and lip movements based on external audio input.
- Lip-Synced - Aligns a speaker's lip movements in a video to a target audio track using latent diffusion techniques.
- Data Preprocessing Pipelines - Ships a suite of tools for cleaning, segmenting, and aligning face data to prepare video datasets.
- Synchronization Network Development - Enables the development of synchronization models on custom datasets to establish audio and visual alignment baselines.
- Lip-Sync Accuracy Metrics - Provides confidence-based evaluation to measure the similarity between generated lip motions and target audio patterns.
- Training Configuration Management - Provides a system to manage training parameters and hyperparameters to optimize for hardware memory and video resolutions.
- Synchronization Accuracy Evaluators - Calculates confidence scores and accuracy metrics to measure how well generated lip movements match target audio.
- High Resolution Training - Optimizes the network for higher pixel densities to reduce blurriness and improve visual fidelity.
- Audio Driven Synthesis - Audio-conditioned latent diffusion models for lip synchronization.
Star history
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