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

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Showing 376–400 of 1008 papers

TitleStatusHype
ECSIC: Epipolar Cross Attention for Stereo Image CompressionCode1
Neural Image Compression: Generalization, Robustness, and Spectral BiasesCode1
Extreme Image Compression using Fine-tuned VQGANs—0
ConvNeXt-ChARM: ConvNeXt-based Transform for Efficient Neural Image Compression—0
AICT: An Adaptive Image Compression Transformer—0
Spatially-Adaptive Learning-Based Image Compression with Hierarchical Multi-Scale Latent Spaces—0
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression—0
Text + Sketch: Image Compression at Ultra Low RatesCode1
Color Learning for Image Compression—0
Processing Energy Modeling for Neural Network Based Image Compression—0
Rapid-INR: Storage Efficient CPU-free DNN Training Using Implicit Neural RepresentationCode0
You Can Mask More For Extremely Low-Bitrate Image CompressionCode1
Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression—0
Image storage on synthetic DNA using compressive autoencoders and DNA-adapted entropy coders—0
MQ-Coder inspired arithmetic coder for synthetic DNA data storage—0
Beyond Learned Metadata-based Raw Image ReconstructionCode1
GAN-based Image Compression with Improved RDO Process—0
Exploring Resolution Fields for Scalable Image Compression with Uncertainty GuidanceCode0
Localization of Just Noticeable Difference for Image CompressionCode0
Exploring Effective Mask Sampling Modeling for Neural Image Compression—0
TransTIC: Transferring Transformer-based Image Compression from Human Perception to Machine PerceptionCode1
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations—0
HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods—0
Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion ModelsCode2
High-Fidelity Image Compression with Score-based Generative Models—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