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 676–700 of 1008 papers

TitleStatusHype
A Practical Approach for Rate-Distortion-Perception Analysis in Learned Image Compression—0
M2TR: Multi-modal Multi-scale Transformers for Deepfake DetectionCode1
Microshift: An Efficient Image Compression Algorithm for HardwareCode1
DANICE: Domain adaptation without forgetting in neural image compression—0
Learning-based Compression for Material and Texture Recognition—0
Conditional Coding for Flexible Learned Video Compression—0
Spatiotemporal Entropy Model is All You Need for Learned Video CompressionCode1
Soft then Hard: Rethinking the Quantization in Neural Image Compression—0
Deep learning-based Edge-aware pre and post-processing methods for JPEG compressed images—0
Image Segmentation, Compression and Reconstruction from Edge Distribution Estimation with Random Field and Random Cluster Theories—0
A Decade of Research for Image Compression In Multimedia Laboratory—0
BlinQS: Blind Quality Scalable Image Compression Algorithm without using PCRD Optimization—0
Learning Scalable _-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression—0
Slimmable Compressive Autoencoders for Practical Neural Image CompressionCode1
Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton—0
Checkerboard Context Model for Efficient Learned Image CompressionCode1
Improved Autoregressive Modeling with Distribution Smoothing—0
Thousand to One: Semantic Prior Modeling for Conceptual Coding—0
End-to-end optimized image compression for multiple machine tasks—0
Generating Images with Sparse RepresentationsCode1
Effects of Image Compression on Face Image Manipulation Detection: A Case Study on Facial Retouching—0
Hierarchical Image Compression Framework—0
On reducing the correlation of bottleneck representations in Autoencoders—0
A Cross Channel Context Model for Latents in Deep Image Compression—0
COIN: COmpression with Implicit Neural representationsCode1
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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