computer-vision-11

MS-SSIM

3260 papers • 126 benchmarks • 313 datasets

A MS-SSIM score helps to analyze how much a De-warping module has been able to de-warp a document image from its initial distorted view.

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Use these libraries to find ms-ssim-11 models and implementations

InterDigitalInc/CompressAI

5 papers 1,035

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Most implemented papers

Variational image compression with a scale hyperprior

Saurabh Singh, J. Ballé, David C. Minnen, S. Hwang, Nick Johnston•Wed Jan 31 2018

It is demonstrated that this model leads to state-of-the-art image compression when measuring visual quality using the popular MS-SSIM index, and yields rate-distortion performance surpassing published ANN-based methods when evaluated using a more traditional metric based on squared error (PSNR).

2149

Content

RenYang-home/OpenDVC

4 papers 204

JooyoungLeeETRI/CA_Entropy_Model

3 papers 141

tensorflow/compression

2 papers 818

FireFYF/SlimCAE

2 papers 45

FireFYF/modulatedautoencoder

2 papers 26

gergely-flamich/relative-entropy-co…

2 papers 15

SaipingZhang/DVC_P

2 papers 10

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End-to-end Optimized Image Compression

J. Ballé, Valero Laparra, Eero P. Simoncelli•Fri Nov 04 2016

Across an independent set of test images, it is found that the optimized method generally exhibits better rate-distortion performance than the standard JPEG and JPEG 2000 compression methods, and a dramatic improvement in visual quality is observed, supported by objective quality estimates using MS-SSIM.

1942 0

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TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network

J. Gamboa, Sheraz Ahmed, Muhammad Zeshan Afzal, Ayushman Dash, M. Liwicki•Sat Mar 18 2017

The TAC-GAN model is trained on the Oxford-102 dataset of flowers, and the discriminability of the generated images with Inception-Score, as well as their diversity using the Multi-Scale Structural Similarity Index (MS-SSIM).

153 0

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DVC: An End-To-End Deep Video Compression Framework

Wanli Ouyang, Dong Xu, Guo Lu, Xiaoyun Zhang, Chunlei Cai, Zhiyong Gao•Thu Nov 29 2018

This paper proposes the first end-to-end video compression deep model that jointly optimizes all the components for video compression, and shows that the proposed approach can outperform the widely used video coding standard H.264 in terms of PSNR and be even on par with the latest standard MS-SSIM.

775 0

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

L. Gool, Radu Timofte, Ren Yang•Sun Jun 28 2020

An open source Tensorflow implementation of the Deep Video Compression (DVC) method, which releases not only the PSNR-optimized re-implementation, denoted by OpenDVC (PSNR), but also the MS-SSIM- Optimized model OpenD VC (MS-SS IM), which provides a more convincing baseline for MS- SSIM optimized methods.

24 0

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Joint Autoregressive and Hierarchical Priors for Learned Image Compression

G. Toderici, J. Ballé, David C. Minnen•Fri Sep 07 2018

It is found that in terms of compression performance, autoregressive and hierarchical priors are complementary and can be combined to exploit the probabilistic structure in the latents better than all previous learned models.

1488 0

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Learned Image Compression With Discretized Gaussian Mixture Likelihoods and Attention Modules

Heming Sun, Zhengxue Cheng, Masaru Takeuchi, J. Katto•Sun Jan 05 2020

This paper proposes to use discretized Gaussian Mixture Likelihoods to parameterize the distributions of latent codes, which can achieve a more accurate and flexible entropy model and achieves a state-of-the-art performance against existing learned compression methods.

1130 0

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Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement

L. Gool, Radu Timofte, Ren Yang, Fabian Mentzer•Tue Mar 03 2020

The experiments validate that the HLVC approach advances the state-of-the-art of deep video compression methods, and outperforms the "Low-Delay P (LDP) very fast" mode of x265 in terms of both PSNR and MS-SSIM.

232 0

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CompressAI: a PyTorch library and evaluation platform for end-to-end compression research

Jean Bégaint, Fabien Racap'e, Simon Feltman, Akshay Pushparaja•Wed Nov 04 2020

CompressAI is presented, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs and is intended to be soon extended to the video compression domain.

508 0

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DSSLIC: Deep Semantic Segmentation-based Layered Image Compression

Mohammad Akbari, Jie Liang, Jingning Han•Thu Jun 07 2018

A deep semantic segmentation-based layered image compression framework in which the segmentation map of the input image is obtained and encoded as the base layer of the bit-stream, which outperforms the H.265/HEVC-based BPG and other codecs in both PSNR and MS-SSIM metrics in RGB domain.

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