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# Single Forward Video Generation Model

## Supplementary Material

- Qualitative Results
- Comparisons
- Ablation Results
- Demo

## Qualitative Results

In this section, we provide more qualitative results of our method on video generation.

## Comparisons

In this section, we provide video comparison results of our method with others as mentioned in the paper.

SVD[2] 25 steps | SVD[2] 16 steps | SVD[2] 8 steps | AnimateLCM[1] 4 steps | Ours

## Ablation Results

In this section, we provide video ablation results as mentioned in the paper.

P_{mean} = -2 | P_{mean} = -1 | P_{mean} = 0 | P_{mean} = 1
P_{std} = -1 | P_{std} = -1 | P_{std} = 1 | P_{std} = 1

## Demo

In this section, we provide a screen recording demo showing the efficiency of our method.

## References

[1] Wang, Fu-Yun, Zhaoyang Huang, Xiaoyu Shi, Weikang Bian, Guanglu Song, Yu Liu, and Hongsheng Li. "AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning." arXiv preprint arXiv:2402.00769 (2024).

[2] Blattmann, Andreas, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi et al. "Stable video diffusion: Scaling latent video diffusion models to large datasets." arXiv preprint arXiv:2311.15127 (2023).