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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 351–400 of 1008 papers

TitleStatusHype
Transformer-based Image Compression with Variable Image Quality Objectives—0
Neural Image Compression Using Masked Sparse Visual Representation—0
Multi-spectral Entropy Constrained Neural Compression of Solar Imagery—0
Multi-Context Dual Hyper-Prior Neural Image Compression—0
Implicit Neural Multiple Description for DNA-based data storage—0
COMPASS: High-Efficiency Deep Image Compression with Arbitrary-scale Spatial Scalability—0
HAT: Hybrid Attention Transformer for Image RestorationCode3
Bandwidth-efficient Inference for Neural Image Compression—0
EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic SegmentationCode1
Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation—0
An Improved Upper Bound on the Rate-Distortion Function of ImagesCode1
Everyone Can Attack: Repurpose Lossy Compression as a Natural Backdoor Attack—0
Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance—0
Image Coding for Machines with Object Region Learning—0
Efficient Learned Lossless JPEG Recompression—0
CompaCT: Fractal-Based Heuristic Pixel Segmentation for Lossless Compression of High-Color DICOM Medical ImagesCode0
Enhanced Residual SwinV2 Transformer for Learned Image Compression—0
RFD-ECNet: Extreme Underwater Image Compression with Reference to Feature DictionarCode0
Dynamic Kernel-Based Adaptive Spatial Aggregation for Learned Image Compression—0
Conditional Perceptual Quality Preserving Image Compression—0
Dynamic Low-Rank Instance Adaptation for Universal Neural Image CompressionCode1
End-to-End Optimization of JPEG-Based Deep Learning Process for Image Classification—0
Frequency Disentangled Features in Neural Image Compression—0
MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image CompressionCode1
A3D: Adaptive, Accurate, and Autonomous Navigation for Edge-Assisted Drones—0
ECSIC: Epipolar Cross Attention for Stereo Image CompressionCode1
Neural Image Compression: Generalization, Robustness, and Spectral BiasesCode1
Extreme Image Compression using Fine-tuned VQGANs—0
ConvNeXt-ChARM: ConvNeXt-based Transform for Efficient Neural Image Compression—0
AICT: An Adaptive Image Compression Transformer—0
Spatially-Adaptive Learning-Based Image Compression with Hierarchical Multi-Scale Latent Spaces—0
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression—0
Text + Sketch: Image Compression at Ultra Low RatesCode1
Color Learning for Image Compression—0
Processing Energy Modeling for Neural Network Based Image Compression—0
Rapid-INR: Storage Efficient CPU-free DNN Training Using Implicit Neural RepresentationCode0
You Can Mask More For Extremely Low-Bitrate Image CompressionCode1
Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression—0
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
Beyond Learned Metadata-based Raw Image ReconstructionCode1
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
TransTIC: Transferring Transformer-based Image Compression from Human Perception to Machine PerceptionCode1
Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations—0
HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods—0
Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion ModelsCode2
High-Fidelity Image Compression with Score-based Generative Models—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