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 551–575 of 1008 papers

TitleStatusHype
Real-Time Adaptive Image Compression—0
Recoding Color Transfer as a Color Homography—0
Recognition-Aware Learned Image Compression—0
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations—0
Reduced bit median quantization: A middle process for Efficient Image Compression—0
Reducing Redundancy in the Bottleneck Representation of the Autoencoders—0
Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression—0
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression—0
Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing—0
Region of Interest based Medical Image Compression—0
Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding—0
Regularized Flexible Activation Function Combinations for Deep Neural Networks—0
Relative Pixel Prediction For Autoregressive Image Generation—0
Representing Images in 200 Bytes: Compression via Triangulation—0
ResiComp: Loss-Resilient Image Compression via Dual-Functional Masked Visual Token Modeling—0
Rethinking Image Compression on the Web with Generative AI—0
Rethinking Learned Image Compression: Context is All You Need—0
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding—0
Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior—0
Robustly overfitting latents for flexible neural image compression—0
Robust Singular Values based on L1-norm PCA—0
ROI-based Deep Image Compression with Swin Transformers—0
RQAT-INR: Improved Implicit Neural Image Compression—0
Saliency-aware End-to-end Learned Variable-Bitrate 360-degree Image Compression—0
Saliency-Driven Hierarchical Learned Image 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