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 851–875 of 1008 papers

TitleStatusHype
DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression—0
Deep Image Compression Using Scene Text Quality Assessment—0
Deep Learning-based Image Compression with Trellis Coded Quantization—0
Deep Lossless Image Compression via Masked Sampling and Coarse-to-Fine Auto-Regression—0
Deep Networks for Compressed Image Sensing—0
DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework—0
Deep Perceptual Compression—0
Deep Perceptual Image Quality Assessment for Compression—0
Deep Predictive Video Compression with Bi-directional Prediction—0
Deep Generative Video Compression—0
Deep Probabilistic Video Compression—0
Deep Sampling Networks—0
Deep Selector-JPEG: Adaptive JPEG Image Compression for Computer Vision in Image classification with Human Vision Criteria—0
DeepSIC: Deep Semantic Image Compression—0
Deep Spatial and Tonal Data Optimisation for Homogeneous Diffusion Inpainting—0
Deep Stereo Image Compression via Bi-Directional Coding—0
Deformation Aware Image Compression—0
Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression—0
MALICE: Manipulation Attacks on Learned Image ComprEssion—0
Dense residual Transformer for image denoising—0
Descriptive analysis of computational methods for automating mammograms with practical applications—0
Design an Advance computer-aided tool for Image Authentication and Classification—0
Development of On Board Computer for a Nanosatellite—0
Device Interoperability for Learned Image Compression with Weights and Activations Quantization—0
Diagnosis-oriented Medical Image Compression with Efficient Transfer Learning—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