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 776–800 of 1008 papers

TitleStatusHype
Mosaicked multispectral image compression based on inter- and intra-band correlation—0
MQ-Coder inspired arithmetic coder for synthetic DNA data storage—0
Multi-Context Dual Hyper-Prior Neural Image Compression—0
Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos—0
Multi-Modality Deep Network for Extreme Learned Image Compression—0
Multi-Modality Deep Network for JPEG Artifacts Reduction—0
Multiple Description Convolutional Neural Networks for Image Compression—0
Multiple Hypothesis Colorization—0
Image Segmentation, Compression and Reconstruction from Edge Distribution Estimation with Random Field and Random Cluster Theories—0
Multiplierless 16-point DCT Approximation for Low-complexity Image and Video Coding—0
Multirate Neural Image Compression with Adaptive Lattice Vector Quantization—0
Multi-Sample Training for Neural Image Compression—0
Multi-scale and Context-adaptive Entropy Model for Image Compression—0
Multiscale Augmented Normalizing Flows for Image Compression—0
Multiscale Feature Importance-based Bit Allocation for End-to-End Feature Coding for Machines—0
Multi-Scale Feature Prediction with Auxiliary-Info for Neural Image Compression—0
Multi-spectral Entropy Constrained Neural Compression of Solar Imagery—0
Multispectral Image Compression Based on HEVC Using Pel-Recursive Inter-Band Prediction—0
Multi-threaded composition of finite-state-automata—0
Near-lossless _-constrained Image Decompression via Deep Neural Network—0
Neural 3D Scene Compression via Model Compression—0
Neural-based Compression Scheme for Solar Image Data—0
Neural Compression of Atmospheric States—0
Neural Graphics Texture Compression Supporting Random Access—0
Neural Image Compression Using Masked Sparse Visual Representation—0
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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