Papers › NeRV: Neural Representations for Videos

NeRV: Neural Representations for Videos

26 Oct 2021NeurIPS 2021 12arXiv:2110.13903archive 2025-07-28

Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava

We propose a novel neural representation for videos (NeRV) which encodes videos in neural networks. Unlike conventional representations that treat videos as frame sequences, we represent videos as neural networks taking frame index as input. Given a frame index, NeRV outputs the corresponding RGB image. Video encoding in NeRV is simply fitting a neural network to video frames and decoding process is a simple feedforward operation. As an image-wise implicit representation, NeRV output the whole image and shows great efficiency compared to pixel-wise implicit representation, improving the encoding speed by 25x to 70x, the decoding speed by 38x to 132x, while achieving better video quality. With such a representation, we can treat videos as neural networks, simplifying several video-related tasks. For example, conventional video compression methods are restricted by a long and complex pipeline, specifically designed for the task. In contrast, with NeRV, we can use any neural network compression method as a proxy for video compression, and achieve comparable performance to traditional frame-based video compression approaches (H.264, HEVC \etc). Besides compression, we demonstrate the generalization of NeRV for video denoising. The source code and pre-trained model can be found at https://github.com/haochen-rye/NeRV.git.

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Code

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haochen-rye/nerv officialmentioned in papermentioned on GitHubpytorch report
ihaeyong/pfnr mentioned on GitHubpytorch report
ihaeyong/pnr mentioned on GitHubpytorchMIT report

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2ran · our draft was wrong
2ran · fixture could not drive it
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CustomConv haochen-rye/nerv/model_nerv.py official repository ran · metamorphic tier: deterministic no licence file found · pointer only · 9d65ce7dcfde9d6e · report
Generator haochen-rye/nerv/model_nerv.py official repository ran · metamorphic tier: deterministic no licence file found · pointer only · 997cab7ed0c74725 · report
MLP haochen-rye/NeRV/model_nerv.py official repository ran · fixture could not drive it no licence file found · pointer only · a44ae0bc9c98e926 · report
NeRVBlock haochen-rye/nerv/model_nerv.py official repository ran · metamorphic tier: deterministic no licence file found · pointer only · 2bf83aaa42382030 · report
ActivationLayer haochen-rye/NeRV/model_nerv.py official repository unverified no licence file found · pointer only · bab299b09f52a8de · report
NormLayer haochen-rye/NeRV/model_nerv.py official repository unverified no licence file found · pointer only · a764487191cdbab5 · report
evaluate haochen-rye/NeRV/train_nerv.py official repository unverified no licence file found · pointer only · 4bcdec64794c3fab · report
ActivationLayer identical code first harvested elsewhere ran · our draft was wrong licence of this copy not recorded · 878fd412e7a78234 · report
MLP identical code first harvested elsewhere ran · fixture could not drive it licence of this copy not recorded · 4b4bad794e3e1cab · report
NormLayer identical code first harvested elsewhere ran · our draft was wrong licence of this copy not recorded · 853ab1b19577355a · report

Tasks

DenoisingNeural Network CompressionVideo CompressionVideo DenoisingVideo Reconstruction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Video Reconstruction UVG NeRV Average PSNR (dB) 34.49 #7 of 7 Archive leaderboard report
Video Reconstruction UVG NeRV Model Size (M) 13.01M #7 of 7 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

SPEED

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