Research map / Video / Video generation
Video Diffusion Models
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add 8 independent image frames per video (joint image-video training) (ablation) | text-to-video diffusion · Text-to-video 16x64x64 | FVD: 202.28 -> 57.84 | Helped |
| increase classifier-free guidance weight 1.0 -> 5.0 (ablation) | text-to-video diffusion · Text-to-video frameskip 1 | IS-avg: 10.80 -> 14.80 | Helped |
| increase classifier-free guidance weight 1.0 -> 5.0 (ablation) | text-to-video diffusion · Text-to-video frameskip 1 | FVD: 41.65 -> 163.74 | Hurt |
| reconstruction guidance instead of replacement for conditioning (ablation) | autoregressive extension · 64x64x64 generation | FVD: 451.45 -> 136.22 | Helped |
| Langevin sampler instead of ancestral (ablation) | Video Diffusion · Kinetics-600 | FVD: 18.6 -> 16.2 | Helped |
| video diffusion vs prior GAN/AR methods | video generation · BAIR Robot Pushing | FVD: 86.9 -> 66.92 | Helped |
Closest papers by meaning
- Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition (ICLR 2024 · similarity 0.92)
- Grid Diffusion Models for Text-to-Video Generation (CVPR 2024 · similarity 0.92)
- From Slow Bidirectional to Fast Autoregressive Video Diffusion Models (CVPR 2025 · similarity 0.92)
- AR-Diffusion: Asynchronous Video Generation with Auto-Regressive Diffusion (CVPR 2025 · similarity 0.92)
- Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation (ICLR 2025 · similarity 0.91)
- FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention (NeurIPS 2024 · similarity 0.91)
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