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OpenDVC: An Open Source Implementation of the DVC Video Compression Method

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arxiv 2006.15862 v2 pith:65OBFA7G submitted 2020-06-29 eess.IV cs.CV

classification eess.IVcs.CV
keywords opendvccompressionvideoms-ssimoptimizedpsnrsourcecodes
verification ladder T0 review T1 audit T2 compute T3 formal
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We introduce an open source Tensorflow implementation of the Deep Video Compression (DVC) method in this technical report. DVC is the first end-to-end optimized learned video compression method, achieving better MS-SSIM performance than the Low-Delay P (LDP) very fast setting of x265 and comparable PSNR performance with x265 (LDP very fast). At the time of writing this report, several learned video compression methods are superior to DVC, but currently none of them provides open source codes. We hope that our OpenDVC codes are able to provide a useful model for further development, and facilitate future researches on learned video compression. Different from the original DVC, which is only optimized for PSNR, we release not only the PSNR-optimized re-implementation, denoted by OpenDVC (PSNR), but also the MS-SSIM-optimized model OpenDVC (MS-SSIM). Our OpenDVC (MS-SSIM) model provides a more convincing baseline for MS-SSIM optimized methods, which can only compare with the PSNR optimized DVC in the past. The OpenDVC source codes and pre-trained models are publicly released at https://github.com/RenYang-home/OpenDVC.

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Cited by 2 Pith papers

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    cs.RO 2026-08 reject novelty 5.0 of 10

    TempoWAM adapts the replanning frequency of world action models based on an online estimate of task progress, reducing inference calls on easy tasks and improving success on hard tasks.

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    OpenDCVCs provides a unified, training-ready PyTorch implementation of DCVC, DCVC-TCM, DCVC-HEM, and DCVC-DC, with benchmarking showing OpenDCVC-DC besting the official DCVC anchor by an average BD-Rate of -59.93%.

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