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 151–175 of 1008 papers

TitleStatusHype
Learning Accurate Entropy Model with Global Reference for Image CompressionCode1
Compressing Images by Encoding Their Latent Representations with Relative Entropy CodingCode1
Learning to Improve Image Compression without Changing the Standard DecoderCode1
Fidelity-Controllable Extreme Image Compression with Generative Adversarial NetworksCode1
Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed SensingCode1
Channel-wise Autoregressive Entropy Models for Learned Image CompressionCode1
Channel-Level Variable Quantization Network for Deep Image CompressionCode1
Locally Masked Convolution for Autoregressive ModelsCode1
High-Fidelity Generative Image CompressionCode1
Neural Sparse Representation for Image RestorationCode1
Improving Inference for Neural Image CompressionCode1
Variational Quantum Singular Value DecompositionCode1
Comparison of Image Quality Models for Optimization of Image Processing SystemsCode1
Learning Better Lossless Compression Using Lossy CompressionCode1
Learning to Structure an Image with Few ColorsCode1
Learning for Video Compression with Hierarchical Quality and Recurrent EnhancementCode1
Asymmetric Gained Deep Image Compression With Continuous Rate AdaptationCode1
Hierarchical Quantized AutoencodersCode1
Variational Bayesian QuantizationCode1
Learning End-to-End Lossy Image Compression: A BenchmarkCode1
A Unified End-to-End Framework for Efficient Deep Image CompressionCode1
Fast, Compact and Highly Scalable Visual Place Recognition through Sequence-based Matching of Overloaded RepresentationsCode1
Image Segmentation Using Deep Learning: A SurveyCode1
Deep Image Compression using Decoder Side InformationCode1
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention ModulesCode1
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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