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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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Greatest papers with code

End-to-end Optimized Image Compression

5 Nov 2016tensorflow/models

We describe an image compression method, consisting of a nonlinear analysis transformation, a uniform quantizer, and a nonlinear synthesis transformation.

IMAGE COMPRESSION MS-SSIM SSIM

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

5 Nov 2020InterDigitalInc/CompressAI

This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs.

IMAGE COMPRESSION MS-SSIM SSIM VIDEO COMPRESSION

Joint Autoregressive and Hierarchical Priors for Learned Image Compression

NeurIPS 2018 InterDigitalInc/CompressAI

While it is well known that autoregressive models come with a significant computational penalty, we find that in terms of compression performance, autoregressive and hierarchical priors are complementary and, together, exploit the probabilistic structure in the latents better than all previous learned models.

IMAGE COMPRESSION MS-SSIM SSIM

DVC: An End-to-end Deep Video Compression Framework

CVPR 2019 GuoLusjtu/DVC

Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.

MS-SSIM OPTICAL FLOW ESTIMATION SSIM VIDEO COMPRESSION

DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks

ICCV 2019 cvlab-stonybrook/DewarpNet

In this work, we propose DewarpNet, a deep-learning approach for document image unwarping from a single image.

 Ranked #1 on MS-SSIM on DocUNet (using extra training data)

LOCAL DISTORTION MS-SSIM OPTICAL CHARACTER RECOGNITION SSIM

Conditional Probability Models for Deep Image Compression

CVPR 2018 fab-jul/imgcomp-cvpr

During training, the auto-encoder makes use of the context model to estimate the entropy of its representation, and the context model is concurrently updated to learn the dependencies between the symbols in the latent representation.

IMAGE COMPRESSION MS-SSIM QUANTIZATION SSIM

An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy Minimization

30 Dec 2019JooyoungLeeETRI/CA_Entropy_Model

In order to show the effectiveness of our proposed JointIQ-Net, extensive experiments have been performed, and showed that the JointIQ-Net achieves a remarkable performance improvement in coding efficiency in terms of both PSNR and MS-SSIM, compared to the previous learned image compression methods and the conventional codecs such as VVC Intra (VTM 7. 1), BPG, and JPEG2000.

IMAGE COMPRESSION MS-SSIM SSIM

TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network

19 Mar 2017dashayushman/TAC-GAN

In this work, we present the Text Conditioned Auxiliary Classifier Generative Adversarial Network, (TAC-GAN) a text to image Generative Adversarial Network (GAN) for synthesizing images from their text descriptions.

MS-SSIM SSIM

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

29 Jun 2020RenYang-home/HLVC

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.

MS-SSIM SSIM VIDEO COMPRESSION

Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model

24 Jun 2020RenYang-home/HLVC

The experiments show that our approach achieves the state-of-the-art learned video compression performance in terms of both PSNR and MS-SSIM.

MS-SSIM SSIM VIDEO COMPRESSION