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 551–600 of 1008 papers

TitleStatusHype
Real-Time Adaptive Image Compression—0
Recoding Color Transfer as a Color Homography—0
Recognition-Aware Learned Image Compression—0
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations—0
Reduced bit median quantization: A middle process for Efficient Image Compression—0
Reducing Redundancy in the Bottleneck Representation of the Autoencoders—0
Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression—0
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression—0
Refining Coded Image in Human Vision Layer Using CNN-Based Post-Processing—0
Region of Interest based Medical Image Compression—0
Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding—0
Regularized Flexible Activation Function Combinations for Deep Neural Networks—0
Relative Pixel Prediction For Autoregressive Image Generation—0
Representing Images in 200 Bytes: Compression via Triangulation—0
ResiComp: Loss-Resilient Image Compression via Dual-Functional Masked Visual Token Modeling—0
Rethinking Image Compression on the Web with Generative AI—0
Rethinking Learned Image Compression: Context is All You Need—0
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding—0
Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior—0
Robustly overfitting latents for flexible neural image compression—0
Robust Singular Values based on L1-norm PCA—0
ROI-based Deep Image Compression with Swin Transformers—0
RQAT-INR: Improved Implicit Neural Image Compression—0
Saliency-aware End-to-end Learned Variable-Bitrate 360-degree Image Compression—0
Saliency-Driven Hierarchical Learned Image Coding for Machines—0
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
Show:102550
← PrevPage 12 of 21Next →
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