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 501–550 of 1008 papers

TitleStatusHype
Image storage on synthetic DNA using compressive autoencoders and DNA-adapted entropy coders—0
MQ-Coder inspired arithmetic coder for synthetic DNA data storage—0
GAN-based Image Compression with Improved RDO Process—0
Exploring Resolution Fields for Scalable Image Compression with Uncertainty GuidanceCode0
Localization of Just Noticeable Difference for Image CompressionCode0
Exploring Effective Mask Sampling Modeling for Neural Image Compression—0
HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods—0
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations—0
High-Fidelity Image Compression with Score-based Generative Models—0
Random-Access Neural Compression of Material Textures—0
Make Lossy Compression Meaningful for Low-Light ImagesCode0
Deep Image Compression Using Scene Text Quality Assessment—0
VVC+M: Plug and Play Scalable Image Coding for Humans and Machines—0
Generative Adversarial Networks for Spatio-Spectral Compression of Hyperspectral Images—0
DNN-Compressed Domain Visual Recognition with Feature Adaptation—0
ROI-based Deep Image Compression with Swin Transformers—0
Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression—0
Multiscale Augmented Normalizing Flows for Image Compression—0
Multi-Modality Deep Network for JPEG Artifacts Reduction—0
Semantically Structured Image Compression via Irregular Group-Based Decoupling—0
Impact of Image Compression on In Vitro Cell Migration Analysis—0
ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training—0
Learned Focused Plenoptic Image Compression with Microimage Preprocessing and Global AttentionCode0
Multi-Modality Deep Network for Extreme Learned Image Compression—0
LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression—0
M2T: Masking Transformers Twice for Faster Decoding—0
Machine Perception-Driven Image Compression: A Layered Generative Approach—0
Are Visual Recognition Models Robust to Image Compression?—0
LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compression—0
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image CompressionCode0
Improvement of Color Image Analysis Using a New Hybrid Face Recognition Algorithm based on Discrete Wavelets and Chebyshev Polynomials—0
Enhancement of theColor Image Compression Using a New Algorithm based on Discrete Hermite Wavelet Transform—0
Lossless Microarray Image Compression by Hardware Array Compactor—0
Efficient Neural Generation of 4K Masks for Homogeneous Diffusion Inpainting—0
SigVIC: Spatial Importance Guided Variable-Rate Image Compression—0
Multispectral Image Compression Based on HEVC Using Pel-Recursive Inter-Band Prediction—0
RQAT-INR: Improved Implicit Neural Image Compression—0
Comprehensive Comparisons of Uniform Quantization in Deep Image CompressionCode0
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger—0
A study on the use of perceptual hashing to detect manipulation of embedded messages in images—0
Saliency-Driven Hierarchical Learned Image Coding for Machines—0
Data-Efficient Sequence-Based Visual Place Recognition with Highly Compressed JPEG Images—0
JND-Based Perceptual Optimization For Learned Image Compression—0
Effect of Lossy Compression Algorithms on Face Image Quality and Recognition—0
Deep Selector-JPEG: Adaptive JPEG Image Compression for Computer Vision in Image classification with Human Vision Criteria—0
Multistage Spatial Context Models for Learned Image CompressionCode0
Dual-layer Image Compression via Adaptive Downsampling and Spatially Varying Upconversion—0
EVC: Towards Real-Time Neural Image Compression with Mask Decay—0
Hyperspectral Image Compression Using Implicit Neural Representation—0
Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood ModelsCode0
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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