What is LongCat-Video-Avatar
LongCat-Video-Avatar is an audio-driven LongCat character animation model launched by the Meituancharacter animationmodel. The model can generate ultra-realistic, lip-synced long videos while maintaining character identity consistency and natural dynamics. LongCat-Video-Avatar supports multiple generation modes, including audio-text-to-video (AT2V), audio-text-image-to-video (ATI2V), and video continuation. Through techniques such as decoupling audio signals from motion, avoiding repetitive content, and reducing VAE error accumulation, it achieves high-quality, long-duration video generation, and can be used for actor performances, singer dynamics, podcasts, sales presentations, and multi-person interaction scenarios.
LongCat-Video-Avatar's Main Features
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Multi-Mode Video Generation: Supports audio-text-to-video (AT2V), audio-text-image-to-video (ATI2V), and video continuation, meeting the diverse needs of different scenarios.
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Natural Dynamics and Identity Consistency: The model can maintain character identity consistency, generate natural facial expressions, lip sync, and body movements, and maintain natural and smooth conversational behavior in multi-person interaction scenarios.
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High-Quality Video Generation: By decoupling audio signals from motion, it avoids stiff behavior during silence, reduces pixel degradation, and ensures the stability and consistency of long videos.
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Diverse Application Scenarios: Suitable for scenarios such as actor performances, singer showcases, podcasts, and sales presentations, providing high-quality video generation solutions for different fields.
LongCat-Video-Avatar's Technical Principles
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Disentangled Unconditional Guidance: By distinguishing speech signals from overall motion, the model can generate natural body movements even during silent segments, avoiding static behavior caused by over-reliance on speech signals and achieving more natural dynamic expression.
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Reference Skip Attention: This mechanism selectively introduces reference image information, can maintain character identity consistency, prevents the "copy-paste" phenomenon caused by excessive leakage of reference images, and balances visual fidelity and motion diversity.
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Cross-Chunk Latent Stitching: By reducing the redundant VAE decoding-encoding loop in autoregressive generation, it reduces pixel degradation, avoids cumulative errors in long video generation, and ensures video coherence and consistency.
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Unified DiT-based Framework: It adopts an architecture based on the Diffusion Model, can generate ultra-realistic long-duration videos, and supports multiple generation modes, including audio-text-to-video (AT2V), audio-text-image-to-video (ATI2V), and video continuation.
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Multi-Stream Audio Input Support: Supports single-stream or multi-stream audio input, and uses L-ROPE (Learnable Relative Positional Encoding) technology to bind audio and visual information, adapting to complex multi-person interaction scenarios.
LongCat-Video-Avatar's Project Address
- Project Official Website：https://meigen-ai.github.io/LongCat-Video-Avatar/
- GitHub Repository：https://github.com/MeiGen-AI/LongCat-Video-Avatar
- HuggingFace Model Library：https://huggingface.co/meituan-longcat/LongCat-Video-Avatar
LongCat-Video-Avatar's Application Scenarios
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Film and Television Production: Used to generate actors' natural expressions and lip sync, reduce special effects costs, and improve the realism of film and television characters.
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Music and Entertainment: Generates vivid body movements and stage performances for singers and virtual idols, enhancing the visual effects of music videos and virtual performances.
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Content Creation and Education: Generates high-quality videos for streamers and teachers, enhancing the appeal and interactivity of podcasts, video blogs, and online education.
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Business and Sales: The model can generate natural and smooth product demonstrations and virtual customer service videos, improving sales results and brand image.
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Multi-person Interactive Scenarios: The model supports multi-person dialogue and interaction, maintaining natural communication dynamics, suitable for meetings, interviews, and social entertainment.