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 801–850 of 1008 papers

TitleStatusHype
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention ModulesCode1
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding—0
An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy MinimizationCode0
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable ModelsCode0
Scale-wise Convolution for Image RestorationCode1
Computationally Efficient Neural Image Compression—0
CARP: Compression through Adaptive Recursive Partitioning for Multi-dimensional ImagesCode0
BINet: a binary inpainting network for deep patch-based image compressionCode0
Learned Variable-Rate Image Compression with Residual Divisive Normalization—0
Variable Rate Deep Image Compression with Modulated AutoencoderCode0
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication—0
Fourier Spectrum Discrepancies in Deep Network Generated Images—0
Evaluation of Intra-coding based image compression.Code0
ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image CompressionCode0
Multi-scale and Context-adaptive Entropy Model for Image Compression—0
Neural Image Compression via Non-Local Attention Optimization and Improved Context ModelingCode0
Observer Dependent Lossy Image CompressionCode0
Neural Inter-Frame Compression for Video Coding—0
Compression without Quantization—0
Relative Pixel Prediction For Autoregressive Image Generation—0
Non-negative Tensor Patch Dictionary Approaches for Image Compression and Deblurring Applications—0
Human Synthesis and Scene Compositing—0
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis?—0
Generative Inpainting Network Applications on Seismic Image Compression and Non-Uniform Sampling—0
Variable Rate Deep Image Compression With a Conditional Autoencoder—0
A Comprehensive Benchmark for Single Image Compression Artifacts Reduction—0
Customized OCT images compression scheme with deep neural network—0
Neural Image Compression and ExplanationCode0
DSIC: Deep Stereo Image CompressionCode0
Human Perceptual Evaluations for Image Compression—0
An Underparametrized Deep Decoder Architecture for Graph SignalsCode0
Automatic Text Line Segmentation Directly in JPEG Compressed Document Images—0
Deep Perceptual Compression—0
Improved Hybrid Layered Image Compression using Deep Learning and Traditional Codecs—0
Fully Convolutional Network for Removing DCT Artefacts From Images—0
High-throughput Onboard Hyperspectral Image Compression with Ground-based CNN ReconstructionCode0
A Deep Image Compression Framework for Face Recognition—0
Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos—0
Learning Image and Video Compression through Spatial-Temporal Energy Compaction—0
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image CompressionCode0
A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image Compression—0
Simultaneously Learning Architectures and Features of Deep Neural Networks—0
Content Adaptive Optimization for Neural Image Compression—0
Towards Lossless Encoding of SentencesCode0
Attention Based Image Compression Post-Processing Convolutional Neural Network—0
A Compression Objective and a Cycle Loss for Neural Image Compression—0
Generative Imaging and Image Processing via Generative Encoder—0
FPGA-based Binocular Image Feature Extraction and Matching System—0
Compressing Weight-updates for Image Artifacts Removal Neural Networks—0
Two-layer Near-lossless HDR Coding with Backward Compatibility to JPEG—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