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 501–525 of 1008 papers

TitleStatusHype
Lossy Image Compression with Conditional Diffusion ModelsCode1
High-Fidelity Variable-Rate Image Compression via Invertible Activation TransformationCode1
Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image CompressionCode1
Learning sparse auto-encoders for green AI image coding—0
Energy-Aware JPEG Image Compression: A Multi-Objective ApproachCode0
A Secure and Efficient Multi-Object Grasping Detection Approach for Robotic Arms—0
Learned Image Compression with Generalized Octave Convolution and Cross-Resolution Parameter Estimation—0
Learned Distributed Image Compression with Multi-Scale Patch Matching in Feature Domain—0
Semantic Segmentation in Learned Compressed Domain—0
Edge-Aware Extended Star-Tetrix Transforms for CFA-Sampled Raw Camera Image Compression—0
Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression—0
Deep Spatial and Tonal Data Optimisation for Homogeneous Diffusion Inpainting—0
Learned Lossless Image Compression With Combined Autoregressive Models And Attention Modules—0
Lossy Image Compression with Quantized Hierarchical VAEsCode1
Convolutional Neural Network (CNN) to reduce construction loss in JPEG compression caused by Discrete Fourier Transform (DFT)Code1
Learned Lossless JPEG Transcoding via Joint Lossy and Residual Compression—0
Learning to Structure an Image with Few Colors and Beyond—0
RAWtoBit: A Fully End-to-end Camera ISP Network—0
Does lossy image compression affect racial bias within face recognition?—0
Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training—0
A Unified Image Preprocessing Framework For Image Compression—0
Expanded Adaptive Scaling Normalization for End to End Image CompressionCode1
Streaming-capable High-performance Architecture of Learned Image Compression CodecsCode0
Evaluating the Practicality of Learned Image Compression—0
Why Accuracy Is Not Enough: The Need for Consistency in Object Detection—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