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

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Showing 176–200 of 1008 papers

TitleStatusHype
Scale-wise Convolution for Image RestorationCode1
Context-adaptive Entropy Model for End-to-end Optimized Image CompressionCode1
Joint Autoregressive and Hierarchical Priors for Learned Image CompressionCode1
From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image RestorationCode1
Variational image compression with a scale hyperpriorCode1
Efficient Nonlinear Transforms for Lossy Image CompressionCode1
Lossy Image Compression with Compressive AutoencodersCode1
End-to-end Optimized Image CompressionCode1
Full Resolution Image Compression with Recurrent Neural NetworksCode1
Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic InferenceCode0
Explicit Residual-Based Scalable Image Coding for Humans and Machines—0
LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical ImagesCode0
Fast Training-free Perceptual Image Compression—0
ABC: Adaptive BayesNet Structure Learning for Computational Scalable Multi-task Image CompressionCode0
Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images—0
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization—0
Fourier-Modulated Implicit Neural Representation for Multispectral Satellite Image Compression—0
Flexible Mixed Precision Quantization for Learned Image CompressionCode0
Structured Pruning and Quantization for Learned Image CompressionCode0
Your Demands Deserve More Bits: Referring Semantic Image Compression at Ultra-low Bitrate—0
Semantics-Guided Generative Image CompressionCode0
Synonymous Variational Inference for Perceptual Image CompressionCode0
Generative Image Compression by Estimating Gradients of the Rate-variable Feature Distribution—0
Low-Rank Adaptation of Pre-trained Vision Backbones for Energy-Efficient Image Coding for MachineCode0
Accelerating Learned Image Compression Through Modeling Neural Training Dynamics—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