Papers › A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
Xiaotao Hu, Zhewei Huang, Ailin Huang, Jun Xu, Shuchang Zhou
The performance of video prediction has been greatly boosted by advanced deep neural networks. However, most of the current methods suffer from large model sizes and require extra inputs, e.g., semantic/depth maps, for promising performance. For efficiency consideration, in this paper, we propose a Dynamic Multi-scale Voxel Flow Network (DMVFN) to achieve better video prediction performance at lower computational costs with only RGB images, than previous methods. The core of our DMVFN is a differentiable routing module that can effectively perceive the motion scales of video frames. Once trained, our DMVFN selects adaptive sub-networks for different inputs at the inference stage. Experiments on several benchmarks demonstrate that our DMVFN is an order of magnitude faster than Deep Voxel Flow and surpasses the state-of-the-art iterative-based OPT on generated image quality. Our code and demo are available at https://huxiaotaostasy.github.io/DMVFN/.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Video Prediction | Cityscapes | DMVFN | LPIPS | 0.0558 | #1 of 3 | Archive leaderboard | report |
| Video Prediction | Cityscapes | DMVFN | MS-SSIM | 0.9573 | #1 of 3 | Archive leaderboard | report |
| Video Prediction | DAVIS 2017 | DMVFN | LPIPS | 0.0996 | #1 of 2 | Archive leaderboard | report |
| Video Prediction | DAVIS 2017 | DMVFN | MS-SSIM | 0.8397 | #1 of 2 | Archive leaderboard | report |
| Video Prediction | KITTI | DMVFN | LPIPS | 0.1074 | #1 of 3 | Archive leaderboard | report |
| Video Prediction | KITTI | DMVFN | MS-SSIM | 0.8853 | #1 of 3 | Archive leaderboard | report |
| Video Prediction | Vimeo90K | DMVFN | LPIPS | 0.0369 | #2 of 3 | Archive leaderboard | report |
| Video Prediction | Vimeo90K | DMVFN | MS-SSIM | 0.9701 | #2 of 3 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Introduced by this paper: DMVFN
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