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Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation

1 Mar 2023CVPR 2023 1arXiv:2303.00440archive 2025-07-28

Guozhen Zhang, Yuhan Zhu, Haonan Wang, Youxin Chen, Gangshan Wu, LiMin Wang

Effectively extracting inter-frame motion and appearance information is important for video frame interpolation (VFI). Previous works either extract both types of information in a mixed way or elaborate separate modules for each type of information, which lead to representation ambiguity and low efficiency. In this paper, we propose a novel module to explicitly extract motion and appearance information via a unifying operation. Specifically, we rethink the information process in inter-frame attention and reuse its attention map for both appearance feature enhancement and motion information extraction. Furthermore, for efficient VFI, our proposed module could be seamlessly integrated into a hybrid CNN and Transformer architecture. This hybrid pipeline can alleviate the computational complexity of inter-frame attention as well as preserve detailed low-level structure information. Experimental results demonstrate that, for both fixed- and arbitrary-timestep interpolation, our method achieves state-of-the-art performance on various datasets. Meanwhile, our approach enjoys a lighter computation overhead over models with close performance. The source code and models are available at https://github.com/MCG-NJU/EMA-VFI.

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ConvBlock MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · metamorphic tier: deterministic Apache-2.0 (permissive) · a9f0972fc8d657ae · report
CrossScalePatchEmbed MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · metamorphic tier: deterministic Apache-2.0 (permissive) · 4d87dd873dd0cb76 · report
DWConv MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · metamorphic tier: deterministic Apache-2.0 (permissive) · b5607e4cc9098c21 · report
InterFrameAttention MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran Apache-2.0 (permissive) · 5d39fa7b2acea443 · report
Mlp MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · metamorphic tier: deterministic Apache-2.0 (permissive) · 49e7751169736ead · report
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depad_if_needed MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · our draft was wrong fingerprinted Apache-2.0 (permissive) · def44daa823d60b3 · report
pad_if_needed MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · our draft was wrong fingerprinted Apache-2.0 (permissive) · aa39c3cb6f9a4cb6 · report
window_partition MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · fixture could not drive it Apache-2.0 (permissive) · 9641bf1050805151 · report
window_reverse MCG-NJU/EMA-VFI/model/feature_extractor.py official repository ran · fixture could not drive it Apache-2.0 (permissive) · 4b2da073b4d351d3 · report
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Tasks

Video Frame Interpolation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Video Frame Interpolation MSU Video Frame Interpolation EMA-VFI LPIPS 0.022 #4 of 24 Archive leaderboard report
Video Frame Interpolation MSU Video Frame Interpolation EMA-VFI MS-SSIM 0.965 #4 of 24 Archive leaderboard report
Video Frame Interpolation MSU Video Frame Interpolation EMA-VFI PSNR 29.89 #4 of 24 Archive leaderboard report
Video Frame Interpolation MSU Video Frame Interpolation EMA-VFI SSIM 0.953 #4 of 24 Archive leaderboard report
Video Frame Interpolation MSU Video Frame Interpolation EMA-VFI VMAF 71.71 #4 of 24 Archive leaderboard report
Video Frame Interpolation SNU-FILM (easy) EMA-VFI PSNR 39.98 #7 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (easy) EMA-VFI SSIM 0.9910 #7 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (extreme) EMA-VFI PSNR 25.69 #4 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (extreme) EMA-VFI SSIM 0.8661 #4 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (hard) EMA-VFI PSNR 30.94 #4 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (hard) EMA-VFI SSIM 0.9392 #4 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (medium) EMA-VFI PSNR 36.09 #6 of 8 Archive leaderboard report
Video Frame Interpolation SNU-FILM (medium) EMA-VFI SSIM 0.9801 #6 of 8 Archive leaderboard report
Video Frame Interpolation UCF101 EMA-VFI PSNR 35.48 #1 of 19 Archive leaderboard report
Video Frame Interpolation UCF101 EMA-VFI SSIM 0.9701 #1 of 19 Archive leaderboard report
Video Frame Interpolation Vimeo90K EMA-VFI PSNR 36.64 #2 of 23 Archive leaderboard report
Video Frame Interpolation Vimeo90K EMA-VFI SSIM 0.9819 #2 of 23 Archive leaderboard report
Video Frame Interpolation X4K1000FPS EMA-VFI PSNR 31.46 #5 of 20 Archive leaderboard report
Video Frame Interpolation X4K1000FPS-2K EMA-VFI PSNR 32.85 #2 of 4 Archive leaderboard report
Video Frame Interpolation Xiph-2K EMA-VFI PSNR 36.90 #2 of 4 Archive leaderboard report
Video Frame Interpolation Xiph-2K EMA-VFI SSIM 0.945 #2 of 4 Archive leaderboard report
Video Frame Interpolation Xiph-4k EMA-VFI PSNR 34.67 #1 of 3 Archive leaderboard report
Video Frame Interpolation Xiph-4k EMA-VFI SSIM 0.907 #1 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

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformer

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