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 576–600 of 1008 papers

TitleStatusHype
Image Compression and Actionable Intelligence With Deep Neural Networks—0
SC2 Benchmark: Supervised Compression for Split Computing—0
Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision—0
Scalable Facial Image Compression with Deep Feature Reconstruction—0
Scale-Space Flow for End-to-End Optimized Video Compression—0
Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform—0
Self-Organized Variational Autoencoders (Self-VAE) for Learned Image Compression—0
Semantically Structured Image Compression via Irregular Group-Based Decoupling—0
Semantic-assisted image compression—0
Semantic Communication based on Generative AI: A New Approach to Image Compression and Edge Optimization—0
Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression—0
Semantics Disentanglement and Composition for Versatile Codec toward both Human-eye Perception and Machine Vision Task—0
Semantic Segmentation in Learned Compressed Domain—0
Semblance: A Rank-Based Kernel on Probability Spaces for Niche Detection—0
Sensitivity Decouple Learning for Image Compression Artifacts Reduction—0
SG-JND: Semantic-Guided Just Noticeable Distortion Predictor For Image Compression—0
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication—0
SigVIC: Spatial Importance Guided Variable-Rate Image Compression—0
Simultaneously Learning Architectures and Features of Deep Neural Networks—0
SINCO: A Novel structural regularizer for image compression using implicit neural representations—0
Singular Value Decomposition of Images from Scanned Photographic Plates—0
LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression—0
Soft Compression for Lossless Image Coding—0
Soft then Hard: Rethinking the Quantization in Neural Image Compression—0
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations—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