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 301–325 of 1008 papers

TitleStatusHype
Idempotence and Perceptual Image CompressionCode1
TLIC: Learned Image Compression with ROI-Weighted Distortion and Bit Allocation—0
End-to-End Optimized Image Compression with the Frequency-Oriented Transform—0
Exploring Compressed Image Representation as a Perceptual Proxy: A StudyCode7
Progressive Feature Fusion Network for Enhancing Image Quality Assessment—0
LiDAR Depth Map Guided Image Compression Model—0
Efficient Parallel Data Optimization for Homogeneous Diffusion Inpainting of 4K Images—0
Transferable Learned Image Compression-Resistant Adversarial Perturbations—0
Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder—0
ED: Perceptually tuned Enhanced Compression Model—0
Towards High-fidelity Artistic Image Vectorization via Texture-Encapsulated Shape Parameterization—0
Learned Lossless Image Compression based on Bit Plane SlicingCode1
Batch Normalization Alleviates the Spectral Bias in Coordinate Networks—0
Countering Personalized Text-to-Image Generation with Influence Watermarks—0
Generative Latent Coding for Ultra-Low Bitrate Image Compression—0
FFCA-Net: Stereo Image Compression via Fast Cascade Alignment of Side Information—0
Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision—0
The Rate-Distortion-Perception-Classification Tradeoff: Joint Source Coding and Modulation via Inverse-Domain GANs—0
Compact 3D Scene Representation via Self-Organizing Gaussian GridsCode3
Quantized Decoder in Learned Image Compression for Deterministic Reconstruction—0
Unified learning-based lossy and lossless JPEG recompression—0
Hyperspectral Image Compression Using Sampling and Implicit Neural Representations—0
Technical description of the EPFL submission to the JPEG DNA CfP—0
Corner-to-Center Long-range Context Model for Efficient Learned Image Compression—0
Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression—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