MS-SSIM
53 papers with code • 1 benchmarks • 0 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.
Libraries
Use these libraries to find MS-SSIM models and implementationsMost implemented papers
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
JooyoungLeeETRI/CA_Entropy_Model
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ICLR 2019
We propose a context-adaptive entropy model for use in end-to-end optimized image compression.
CAE-ADMM: Implicit Bitrate Optimization via ADMM-based Pruning in Compressive Autoencoders
We introduce ADMM-pruned Compressive AutoEncoder (CAE-ADMM) that uses Alternative Direction Method of Multipliers (ADMM) to optimize the trade-off between distortion and efficiency of lossy image compression.
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
The experiments show that our approach achieves the state-of-the-art learned video compression performance in terms of both PSNR and MS-SSIM.
A Person Re-identification Data Augmentation Method with Adversarial Defense Effect
finger-monkey/ReID_Adversarial_Defense
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This method can not only improve the accuracy of the model, but also help the model defend against adversarial examples; 2) Multi-Modal Defense, it integrates three homogeneous modal images of visible, grayscale and sketch, and further strengthens the defense ability of the model.
End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression
KUIS-AI-Tekalp-Research-Group/video-compression
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Conventional video compression (VC) methods are based on motion compensated transform coding, and the steps of motion estimation, mode and quantization parameter selection, and entropy coding are optimized individually due to the combinatorial nature of the end-to-end optimization problem.
Learning to Generate Images with Perceptual Similarity Metrics
clementchadebec/benchmark_VAE
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We propose instead to use a loss function that is better calibrated to human perceptual judgments of image quality: the multiscale structural-similarity score (MS-SSIM).
High-Resolution Deep Convolutional Generative Adversarial Networks
Generative Adversarial Networks (GANs) convergence in a high-resolution setting with a computational constrain of GPU memory capacity (from 12GB to 24 GB) has been beset with difficulty due to the known lack of convergence rate stability.
Conditional Probability Models for Deep Image Compression
fab-jul/imgcomp-cvpr
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CVPR 2018
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.
PAD-Net: A Perception-Aided Single Image Dehazing Network
In this work, we investigate the possibility of replacing the $\ell_2$ loss with perceptually derived loss functions (SSIM, MS-SSIM, etc.)
DocUNet: Document Image Unwarping via a Stacked U-Net
teresasun/docUnet.pytorch
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CVPR 2018
The network is trained on this dataset with various data augmentations to improve its generalization ability.
