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 726–750 of 1008 papers

TitleStatusHype
Enhanced Standard Compatible Image Compression Framework based on Auxiliary Codec Networks—0
Learning to Improve Image Compression without Changing the Standard DecoderCode1
Quantifying the effect of image compression on supervised learning applications in optical microscopy—0
Extreme compression of grayscale images—0
Leveraging Domain Knowledge using Machine Learning for Image Compression in Internet-of-Things—0
Fidelity-Controllable Extreme Image Compression with Generative Adversarial NetworksCode1
Lossy Image Compression with Normalizing Flows—0
Optical Flow and Mode Selection for Learning-based Video Coding—0
Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed SensingCode1
Task-Aware Quantization Network for JPEG Image Compression—0
Learning to Learn to Compress—0
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures—0
Regularized Flexible Activation Function Combinations for Deep Neural Networks—0
Accelerating Deep Learning Applications in Space—0
Wireless Image Retrieval at the Edge—0
Full Quaternion Representation of Color images: A Case Study on QSVD-based Color Image Compression—0
Channel-wise Autoregressive Entropy Models for Learned Image CompressionCode1
Channel-Level Variable Quantization Network for Deep Image CompressionCode1
C2G-Net: Exploiting Morphological Properties for Image Classification—0
ModeNet: Mode Selection Network For Learned Video Coding—0
Perceptually Optimizing Deep Image Compression—0
Locally Masked Convolution for Autoregressive ModelsCode1
Modeling Lost Information in Lossy Image Compression—0
A Multiparametric Class of Low-complexity Transforms for Image and Video Coding—0
Concatenated Attention Neural Network for Image Restoration—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