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 526–550 of 1008 papers

TitleStatusHype
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression—0
C2G-Net: Exploiting Morphological Properties for Image Classification—0
CALLIC: Content Adaptive Learning for Lossless Image Compression—0
Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net—0
Cascade Decoders-Based Autoencoders for Image Reconstruction—0
CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression—0
CBANet: Towards Complexity and Bitrate Adaptive Deep Image Compression using a Single Network—0
Channel-wise Feature Decorrelation for Enhanced Learned Image Compression—0
CIC: Circular Image Compression—0
Clustering-Based Quantisation for PDE-Based Image Compression—0
CMamba: Learned Image Compression with State Space Models—0
Coding Standards as Anchors for the CVPR CLIC video track—0
Color Learning for Image Compression—0
Combined Approach for Image Segmentation—0
Combining Progressive Image Compression and Random Access in DNA Data Storage—0
Bridging Compressed Image Latents and Multimodal Large Language Models—0
Compact Latent Representation for Image Compression (CLRIC)—0
Comparison of Lossless Image Formats—0
COMPASS: High-Efficiency Deep Image Compression with Arbitrary-scale Spatial Scalability—0
Compressed image quality assessment using stacking—0
Compressed sensing of astronomical images:orthogonal wavelets domains—0
Compressible and Searchable: AI-native Multi-Modal Retrieval System with Learned Image Compression—0
Compressing high-resolution data through latent representation encoding for downscaling large-scale AI weather forecast model—0
Compressing Weight-updates for Image Artifacts Removal Neural Networks—0
Compression-Resistant Backdoor Attack against Deep Neural Networks—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