Mini Sora 开源社区定位为由社区同学自发组织的开源社区（免费不收取任何费用、不割韭菜），Mini Sora 计划探索实现 Sora 的实现路径可发展可能：
- 将定期举办 Sora 的圆桌和社区一起探讨可能性
- 视频生成的现有技术路径探讨
| 论文 |
链接 |
| 1) Guided-Diffusion: Diffusion Models Beat GANs on Image Synthesis |
Paper, Github |
| 2) Latent Diffusion: High-Resolution Image Synthesis with Latent Diffusion Models |
Paper, Github |
| 3) EDM: Elucidating the Design Space of Diffusion-Based Generative Models |
Paper, Github |
| 4) DDPM: Denoising Diffusion Probabilistic Models |
Paper, Github |
| 5) DDIM: Denoising Diffusion Implicit Models |
Paper, Github |
| 6) Score-Based Diffusion: Score-Based Generative Modeling through Stochastic Differential Equations |
Paper, Github |
| 论文 |
链接 |
| 1) UViT: All are Worth Words: A ViT Backbone for Diffusion Models |
Paper, Github, ModelScope |
| 2) DiT: Scalable Diffusion Models with Transformers |
Paper, Github, ModelScope |
| 3) SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers |
Paper, Github, ModelScope |
| 4) FiT: Flexible Vision Transformer for Diffusion Model |
Paper, Github |
| 论文 |
链接 |
| 1) Animatediff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning |
Paper, Github, ModelScope |
| 2) I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models |
Paper, Github, ModelScope |
| 4) Imagen Video: High Definition Video Generation with Diffusion Models |
Paper |
| 5) MoCoGAN: Decomposing Motion and Content for Video Generation |
Paper |
| 6) Adversarial Video Generation on Complex Datasets |
Paper |
| 7) Photorealistic Video Generation with Diffusion Models |
Paper |
| 8) VideoGPT: Video Generation using VQ-VAE and Transformers |
Paper, Github |
| 9) Video Diffusion Models |
Paper, Github, Project |
| 10) MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation |
Paper, Github, Project, Blog |
| 论文 |
链接 |
| 1) World Model on Million-Length Video And Language With RingAttention |
Paper, Github |
| 2) Ring Attention with Blockwise Transformers for Near-Infinite Context |
Paper, Github |
| 3) Extending LLMs' Context Window with 100 Samples |
Paper, Github |
| 4) Efficient Streaming Language Models with Attention Sinks |
Paper, Github |
| 5) The What, Why, and How of Context Length Extension Techniques in Large Language Models – A Detailed Survey |
Paper |
| Paper |
Links |
| 1) ViViT: A Video Vision Transformer |
Paper, Github |
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