SOTAVerified

Image Compression

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 801–825 of 1008 papers

TitleStatusHype
Improved Image Coding Autoencoder With Deep Learning—0
Generalized Octave Convolutions for Learned Multi-Frequency Image CompressionCode0
Binary Probability Model for Learning Based Image Compression—0
STW and SPIHT Wavelet compression using MATLAB wavelet Tool for Color Image—0
Discernible Image Compression—0
Saliency Driven Perceptual Image Compression—0
Ultra High Fidelity Image Compression with _-constrained Encoding and Deep Decoding—0
A Hybrid Quantum enabled RBM Advantage: Convolutional Autoencoders For Quantum Image Compression and Generative Learning—0
Deep Learning-based Image Compression with Trellis Coded Quantization—0
A GAN-based Tunable Image Compression System—0
SUR-FeatNet: Predicting the Satisfied User Ratio Curvefor Image Compression with Deep Feature LearningCode0
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding—0
An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy MinimizationCode0
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable ModelsCode0
Computationally Efficient Neural Image Compression—0
CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional ImagesCode0
BINet: a binary inpainting network for deep patch-based image compressionCode0
Variable Rate Deep Image Compression with Modulated AutoencoderCode0
Learned Variable-Rate Image Compression with Residual Divisive Normalization—0
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication—0
Fourier Spectrum Discrepancies in Deep Network Generated Images—0
Evaluation of Intra-coding based image compression.Code0
ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image CompressionCode0
Multi-scale and Context-adaptive Entropy Model for Image Compression—0
Neural Image Compression via Non-Local Attention Optimization and Improved Context ModelingCode0
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All datasetskodakImageNet32BSDS500Caltech101Cars-196CIFAR-10FER2013Food-101Oxford-IIIT Pet DatasetPCamSTL-10

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1STFBD-Rate over VTM-17.0-2.48—Unverified
2WACNNBD-Rate over VTM-17.0-2.95—Unverified
3ELICBD-Rate over VTM-17.0-5.95—Unverified
4MLICBD-Rate over VTM-17.0-8.05—Unverified
5SegPICBD-Rate over VTM-17.0-8.18—Unverified
6LIC-TCM LargeBD-Rate over VTM-17.0-10.14—Unverified
7MLIC+BD-Rate over VTM-17.0-11.39—Unverified
8MLIC++BD-Rate over VTM-17.0-13.39—Unverified
#ModelMetricClaimedVerifiedStatus
1PNGbpsp6.42—Unverified
2JPEG2000bpsp6.35—Unverified
3L3Cbpsp4.76—Unverified
4MS-PixelCNNbpsp3.95—Unverified
5iFlowbpsp3.88—Unverified
#ModelMetricClaimedVerifiedStatus
1RK-CCSNetAverage PSNR30.51—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,340—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,470—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,410—Unverified
#ModelMetricClaimedVerifiedStatus
1SUDHEER10%1—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,270—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,210—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,490—Unverified
#ModelMetricClaimedVerifiedStatus
1Lossyless CompressorBit rate1,340—Unverified