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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

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Latest papers without code

An Implementation of Vector Quantization using the Genetic Algorithm Approach

16 Feb 2021

The application of machine learning(ML) and genetic programming(GP) to the image compression domain has produced promising results in many cases.

IMAGE COMPRESSION QUANTIZATION

Discrete Cosine Transform in JPEG Compression

13 Feb 2021

Via an intensive literature study, this paper first introduces DCT and JPEG Compression.

IMAGE COMPRESSION

Progressive Neural Image Compression with Nested Quantization and Latent Ordering

4 Feb 2021

We present PLONQ, a progressive neural image compression scheme which pushes the boundary of variable bitrate compression by allowing quality scalable coding with a single bitstream.

IMAGE COMPRESSION QUANTIZATION

Overfitting for Fun and Profit: Instance-Adaptive Data Compression

ICLR 2021

At a high level, neural compression is based on an autoencoder that tries to reconstruct the input instance from a (quantized) latent representation, coupled with a prior that is used to losslessly compress these latents.

IMAGE COMPRESSION QUANTIZATION

Improved Autoregressive Modeling with Distribution Smoothing

ICLR 2021

While autoregressive models excel at image compression, their sample quality is often lacking.

ADVERSARIAL DEFENSE DENSITY ESTIMATION IMAGE COMPRESSION

Learned Multi-Resolution Variable-Rate Image Compression with Octave-based Residual Blocks

31 Dec 2020

Recently deep learning-based image compression has shown the potential to outperform traditional codecs.

IMAGE COMPRESSION QUANTIZATION

Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality

19 Dec 2020

As the existing HDR quality datasets are limited in size, we created a Unified Photometric Image Quality dataset (UPIQ) with over 4, 000 images by realigning and merging existing HDR and standard-dynamic-range (SDR) datasets.

IMAGE COMPRESSION

Learned Block-based Hybrid Image Compression

17 Dec 2020

Recent works on learned image compression perform encoding and decoding processes in a full-resolution manner, resulting in two problems when deployed for practical applications.

IMAGE COMPRESSION MS-SSIM SSIM

Learned Video Codec with Enriched Reconstruction for CLIC P-frame Coding

14 Dec 2020

More specifically, we designed a compressor network with Refine-Net for coding residual signals and motion vectors.

IMAGE COMPRESSION MOTION ESTIMATION

How to Exploit the Transferability of Learned Image Compression to Conventional Codecs

3 Dec 2020

Recent research suggests that generative adversarial networks have the ability to overcome this limitation and serve as a multi-modal loss, especially for textures.

IMAGE COMPRESSION MS-SSIM SSIM