SOTAVerified

MS-SSIM

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.

Papers

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Showing 126–150 of 179 papers

TitleStatusHype
Emulation of cosmological mass maps with conditional generative adversarial networks—0
Feedback Recurrent Autoencoder for Video Compression—0
Learning for Video Compression with Hierarchical Quality and Recurrent EnhancementCode1
Asymmetric Gained Deep Image Compression With Continuous Rate AdaptationCode1
Improved Image Coding Autoencoder With Deep Learning—0
Generalized Octave Convolutions for Learned Multi-Frequency Image CompressionCode0
Saliency Driven Perceptual Image Compression—0
A GAN-based Tunable Image Compression System—0
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention ModulesCode1
An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy MinimizationCode0
Multi-scale and Context-adaptive Entropy Model for Image Compression—0
Neural Image Compression via Non-Local Attention Optimization and Improved Context ModelingCode0
Observer Dependent Lossy Image CompressionCode0
Image Super-Resolution Improved by Edge InformationCode0
DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression NetworksCode0
DeepObfuscator: Obfuscating Intermediate Representations with Privacy-Preserving Adversarial Learning on Smartphones—0
Customized OCT images compression scheme with deep neural network—0
Human Perceptual Evaluations for Image Compression—0
Deep Perceptual Compression—0
Improved Hybrid Layered Image Compression using Deep Learning and Traditional Codecs—0
Learning Image and Video Compression through Spatial-Temporal Energy Compaction—0
Attention Based Image Compression Post-Processing Convolutional Neural Network—0
A Compression Objective and a Cycle Loss for Neural Image Compression—0
Adaptive Sample-space & Adaptive Probability coding: a neural-network based approach for compression—0
Non-local Attention Optimized Deep Image Compression—0
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