About
Image Compression is an application of data compression for digital images to lower their storage and/or transmission requirements.
Source: Variable Rate Deep Image Compression With a Conditional Autoencoder
Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Subtasks
Greatest papers with code
Full Resolution Image Compression with Recurrent Neural Networks
CVPR 2017
• tensorflow/models
• 
As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the aid of entropy coding.
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.
Lossless Image Compression through Super-Resolution
• caoscott/SReC
• 
We introduce a simple and efficient lossless image compression algorithm.
High-Fidelity Generative Image Compression
NeurIPS 2020
• tensorflow/compression
•
We extensively study how to combine Generative Adversarial Networks and learned compression to obtain a state-of-the-art generative lossy compression system.
Generative Adversarial Networks for Extreme Learned Image Compression
ICLR 2019
• Justin-Tan/generative-compression
•
We present a learned image compression system based on GANs, operating at extremely low bitrates.
Residual Dense Network for Image Restoration
• yulunzhang/RDN
•
We fully exploit the hierarchical features from all the convolutional layers.
Ranked #1 on
Color Image Denoising
on Kodak24 sigma30
DEBLURRING IMAGE COMPRESSION IMAGE COMPRESSION ARTIFACT REDUCTION IMAGE DENOISING IMAGE RESTORATION IMAGE SUPER-RESOLUTION
"Zero-Shot" Super-Resolution using Deep Internal Learning
On such images, our method outperforms SotA CNN-based SR methods, as well as previous unsupervised SR methods.
Ranked #30 on
Image Super-Resolution
on BSD100 - 4x upscaling
Practical Full Resolution Learned Lossless Image Compression
CVPR 2019
• fab-jul/L3C-PyTorch
•
We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000.
Ranked #2 on
Image Compression
on ImageNet32
Variational Quantum Singular Value Decomposition
In this work, we propose a variational quantum algorithm for singular value decomposition (VQSVD).
Semantic Perceptual Image Compression using Deep Convolution Networks
• iamaaditya/image-compression-cnn
•
Here, we present a powerful cnn tailored to the specific task of semantic image understanding to achieve higher visual quality in lossy compression.