Autoregressive Video Generation without Vector Quantization

This is the text2image demo, see text2video demo here.

We present NOVA (NOn-Quantized Video Autoregressive Model), a model that enables autoregressive image/video generation with high efficiency. NOVA reformulates the video generation problem as non-quantized autoregressive modeling of temporal frame-by-frame prediction and spatial set-by-set prediction. NOVA generalizes well and enables diverse zero-shot generation abilities in one unified model.

✨Hightlights

• 🔥 Novel Approach: Non-quantized video autoregressive generation.
• 🔥 State-of-the-art Performance: High efficiency with state-of-the-art t2i/t2v results.
• 🔥 Unified Modeling: Multi-task capabilities in a single unified model.

Citation

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@article{deng2024nova,
  title={Autoregressive Video Generation without Vector Quantization},
  author={Deng, Haoge and Pan, Ting and Diao, Haiwen and Luo, Zhengxiong and Cui, Yufeng and Lu, Huchuan and Shan, Shiguang and Qi, Yonggang and Wang, Xinlong},
  journal={arXiv preprint arXiv:2412.14169},
  year={2024}
}

Acknowledgement

We thank the repositories: MAE, MAR, MaskGIT, DiT, Open-Sora-Plan, CogVideo, and CodeWithGPU.

License

Code and models are licensed under Apache License 2.0.