StableAvatar

StableAvatar is an end-to-end video diffusion transformer designed for generating infinite-length, high-quality audio-driven avatar videos. It is intended for users who need to create realistic and synchronized avatar videos based on reference images and audio inputs. StableAvatar's architecture integrates an Audio Adapter and a novel Time-step-aware Audio Adapter to prevent error accumulation and enhance audio synchronization.

StableAvatar works by first extracting audio embeddings from the input audio using Wav2Vec. These embeddings are then fed into the Audio Adapter, which injects the outputs into the video diffusion transformer via cross-attention. This process enables the model to synthesize high-quality avatar videos that are synchronized with the input audio. The model also introduces a Dynamic Weighted Sliding-window Strategy to fuse latent representations over time, enhancing the smoothness of the generated videos.

The users who get the most value from StableAvatar are those who require high-quality, infinite-length avatar videos for various applications, such as social media, advertising, or entertainment. These users can leverage StableAvatar's capabilities to create realistic and engaging avatar videos that are synchronized with audio inputs, without the need for post-processing or additional tools.