MS-SSIM
37 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
End-to-end Optimized Image Compression
We describe an image compression method, consisting of a nonlinear analysis transformation, a uniform quantizer, and a nonlinear synthesis transformation.
Variational image compression with a scale hyperprior
tensorflow/compression
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ICLR 2018
We describe an end-to-end trainable model for image compression based on variational autoencoders.
DVC: An End-to-end Deep Video Compression Framework
Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network
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.
OpenDVC: An Open Source Implementation of the DVC Video Compression Method
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.
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
InterDigitalInc/CompressAI
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NeurIPS 2018
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.
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.
Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
RenYang-home/HLVC
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CVPR 2020
In our HLVC approach, the hierarchical quality benefits the coding efficiency, since the high quality information facilitates the compression and enhancement of low quality frames at encoder and decoder sides, respectively.
DSSLIC: Deep Semantic Segmentation-based Layered Image Compression
makbari7/DSSLIC
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A compact representation of the input image is also generated and encoded as the first enhancement layer.
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.
