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rename folders to align with model names.
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ustclibin authored and yaohualibin committed Mar 14, 2023
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# Introduction

Official Pytorch implementation for [Neural Video Compression with Diverse Contexts](https://arxiv.org/abs/2302.14402), in CVPR 2023.
Official Pytorch implementation for DCVC-DC: [Neural Video Compression with **D**iverse **C**ontexts](https://arxiv.org/abs/2302.14402), in CVPR 2023.

# Prerequisites
* Python 3.8 and conda, get [Conda](https://www.anaconda.com/)
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# Introduction

Official Pytorch implementation for [Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression](https://arxiv.org/abs/2207.05894), in ACM MM 2022.
Official Pytorch implementation for DCVC-HEM: [**H**ybrid Spatial-Temporal **E**ntropy **M**odelling for Neural Video Compression](https://arxiv.org/abs/2207.05894), in ACM MM 2022.

# Prerequisites
* Python 3.8 and conda, get [Conda](https://www.anaconda.com/)
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# Introduction
* Official Pytorch implementation for [Temporal Context Mining for Learned Video Compression](https://ieeexplore.ieee.org/document/9941493), in IEEE Transactions on Multimedia.
* Official Pytorch implementation for DCVC-TCM: [**T**emporal **C**ontext **M**ining for Learned Video Compression](https://ieeexplore.ieee.org/document/9941493), in IEEE Transactions on Multimedia.
* Arxiv version can be found [here](https://arxiv.org/abs/2111.13850).

# Prerequisites
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# Introduction

Official Pytorch implementation for Neural Video and Image Compression including:
* [Deep Contextual Video Compression](https://proceedings.neurips.cc/paper/2021/file/96b250a90d3cf0868c83f8c965142d2a-Paper.pdf), NeurIPS 2021, in [this folder](./NeurIPS2021/).
* [Temporal Context Mining for Learned Video Compression](https://ieeexplore.ieee.org/document/9941493), in IEEE Transactions on Multimedia, and [arxiv](https://arxiv.org/abs/2111.13850), in [this folder](./TMM_TCMVC/).
* [Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression](https://arxiv.org/abs/2207.05894), ACM MM 2022, in [this folder](./ACMMM2022/).
- The first end-to-end neural video codec to exceed H.266 (VTM) using the highest compression ratio configuration, in terms of both PSNR and MS-SSIM.
- The first end-to-end neural video codec to achieve rate adjustment in single model.
* [Neural Video Compression with Diverse Contexts](https://arxiv.org/abs/2302.14402), CVPR 2023, in [this folder](./CVPR2023/).
- The first end-to-end neural video codec to exceed [ECM](https://jvet-experts.org/doc_end_user/documents/27_Teleconference/wg11/JVET-AA0006-v1.zip) using the highest compression ratio configuration, in terms of PSNR and MS-SSIM for RGB content.
- The first end-to-end neural video codec to exceed ECM using the highest compression ratio configuration, in terms of PSNR for YUV420 content.
* [EVC: Towards Real-Time Neural Image Compression with Mask Decay](https://openreview.net/forum?id=XUxad2Gj40n), ICLR 2023, in [this folder](./ICLR2023).
* Neural Video Codec
* DCVC: [Deep Contextual Video Compression](https://proceedings.neurips.cc/paper/2021/file/96b250a90d3cf0868c83f8c965142d2a-Paper.pdf), NeurIPS 2021, in [this folder](./DCVC/).
* DCVC-TCM: [**T**emporal **C**ontext **M**ining for Learned Video Compression](https://ieeexplore.ieee.org/document/9941493), in IEEE Transactions on Multimedia, and [arxiv](https://arxiv.org/abs/2111.13850), in [this folder](./DCVC-TCM/).
* DCVC-HEM: [**H**ybrid Spatial-Temporal **E**ntropy **M**odelling for Neural Video Compression](https://arxiv.org/abs/2207.05894), ACM MM 2022, in [this folder](./DCVC-HEM/).
- The first end-to-end neural video codec to exceed H.266 (VTM) using the highest compression ratio configuration, in terms of both PSNR and MS-SSIM.
- The first end-to-end neural video codec to achieve rate adjustment in single model.
* DCVC-DC: [Neural Video Compression with **D**iverse **C**ontexts](https://arxiv.org/abs/2302.14402), CVPR 2023, in [this folder](./DCVC-DC/).
- The first end-to-end neural video codec to exceed [ECM](https://jvet-experts.org/doc_end_user/documents/27_Teleconference/wg11/JVET-AA0006-v1.zip) using the highest compression ratio configuration, in terms of PSNR and MS-SSIM for RGB content.
- The first end-to-end neural video codec to exceed ECM using the highest compression ratio configuration, in terms of PSNR for YUV420 content.
* Neural Image Codec
* [EVC: Towards Real-Time Neural Image Compression with Mask Decay](https://openreview.net/forum?id=XUxad2Gj40n), ICLR 2023, in [this folder](./EVC/).

# On the comparison

Please note that different methods may use different configurations to test different models, such as
* Source video may be different, e.g., cropped or padded to the desired resolution.
* Intra period may be different, e.g., 32, 12, or 10.
* Intra period may be different, e.g., 96, 32, 12, or 10.
* Number of encoded frames may be different.

So, it does not make sense to compare the numbers in different methods directly, unless making sure they are using same test conditions.
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