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 1–50 of 1008 papers

TitleStatusHype
Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic InferenceCode0
Explicit Residual-Based Scalable Image Coding for Humans and Machines—0
NIC-RobustBench: A Comprehensive Open-Source Toolkit for Neural Image Compression and Robustness AnalysisCode1
LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical ImagesCode0
DiffO: Single-step Diffusion for Image Compression at Ultra-Low BitratesCode1
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
TokBench: Evaluating Your Visual Tokenizer before Visual Generation—0
Generative Latent Coding for Ultra-Low Bitrate Image and Video Compression—0
OSCAR: One-Step Diffusion Codec for Image Compression Across Multiple Bit-ratesCode1
One-Step Diffusion-Based Image Compression with Semantic Distillation—0
Combining Progressive Image Compression and Random Access in DNA Data Storage—0
GANCompress: GAN-Enhanced Neural Image Compression with Binary Spherical Quantization—0
Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion modelCode0
High Quality Underwater Image Compression with Adaptive Correction and Codebook-based Augmentation—0
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion—0
PICD: Versatile Perceptual Image Compression with Diffusion Rendering—0
Towards Facial Image Compression with Consistency Preserving Diffusion Prior—0
Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images—0
Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs—0
Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields—0
LoC-LIC: Low Complexity Learned Image Coding Using Hierarchical Feature Transforms—0
MLICv2: Enhanced Multi-Reference Entropy Modeling for Learned Image Compression—0
TVC: Tokenized Video Compression with Ultra-Low Bitrate—0
LimitNet: Progressive, Content-Aware Image Offloading for Extremely Weak Devices & NetworksCode0
All-in-One Transferring Image Compression from Human Perception to Multi-Machine Perception—0
Efficient Masked Image Compression with Position-Indexed Self-Attention—0
Universal Representations for Classification-enhanced Lossy Compression—0
3DM-WeConvene: Learned Image Compression with 3D Multi-Level Wavelet-Domain Convolution and Entropy ModelCode1
Subjective Visual Quality Assessment for High-Fidelity Learning-Based Image CompressionCode0
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression—0
Learned Image Compression with Dictionary-based Entropy ModelCode2
Learned Image Compression and Restoration for Digital PathologyCode0
ShiftLIC: Lightweight Learned Image Compression with Spatial-Channel Shift OperationsCode1
Multi-Scale Invertible Neural Network for Wide-Range Variable-Rate Learned Image CompressionCode1
F-INR: Functional Tensor Decomposition for Implicit Neural Representations—0
Bitstream Collisions in Neural Image Compression via Adversarial PerturbationsCode0
Multiscale Feature Importance-based Bit Allocation for End-to-End Feature Coding for Machines—0
TFIC: End-to-End Text-Focused Image Compression for Coding for Machines—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