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 301–325 of 1008 papers

TitleStatusHype
Efficient Progressive Image Compression with Variance-aware MaskingCode0
JPEG AI Image Compression Visual Artifacts: Detection Methods and Dataset—0
Enhancing Learned Image Compression via Cross Window-based AttentionCode0
Conditional Hallucinations for Image Compression—0
Learning Lossless Compression for High Bit-Depth Volumetric Medical Image—0
FIPER: Generalizable Factorized Features for Robust Low-Level Vision Models—0
Test-time adaptation for image compression with distribution regularization—0
Towards Reproducible Learning-based Compression—0
Fine-grained subjective visual quality assessment for high-fidelity compressed imagesCode0
Fast Data-independent KLT Approximations Based on Integer Functions—0
Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression—0
Compressing high-resolution data through latent representation encoding for downscaling large-scale AI weather forecast model—0
JPEG Inspired Deep LearningCode0
Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach—0
GABIC: Graph-based Attention Block for Image CompressionCode0
STanH : Parametric Quantization for Variable Rate Learned Image Compression—0
Learning-Based Image Compression for MachinesCode0
Streaming Neural Images—0
The Effect of Lossy Compression on 3D Medical Images Segmentation with Deep Learning—0
Window-based Channel Attention for Wavelet-enhanced Learned Image Compression—0
Reduced bit median quantization: A middle process for Efficient Image Compression—0
Multi-Scale Feature Prediction with Auxiliary-Info for Neural Image Compression—0
Breaking the Barriers of One-to-One Usage of Implicit Neural Representation in Image Compression: A Linear Combination Approach with Performance GuaranteesCode0
LFIC-DRASC: Deep Light Field Image Compression Using Disentangled Representation and Asymmetrical Strip Convolution—0
Few-Shot Domain Adaptation for Learned Image Compression—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