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
AsymLLIC: Asymmetric Lightweight Learned Image Compression—0
Asymmetric Learned Image Compression with Multi-Scale Residual Block, Importance Map, and Post-Quantization Filtering—0
A Systematic Evaluation of Coding Strategies for Sparse Binary Images—0
A Taxonomy of Miscompressions: Preparing Image Forensics for Neural Compression—0
A Training-Free Defense Framework for Robust Learned Image Compression—0
Attack and Defense Analysis of Learned Image Compression—0
Attention-Based Generative Neural Image Compression on Solar Dynamics Observatory—0
Attention Based Image Compression Post-Processing Convolutional Neural Network—0
Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton—0
A Unified Image Preprocessing Framework For Image Compression—0
Autoencoder based image compression: can the learning be quantization independent?—0
Autoencoders with Variable Sized Latent Vector for Image Compression—0
Automatic Text Line Segmentation Directly in JPEG Compressed Document Images—0
“Zero-Shot” Super-Resolution Using Deep Internal Learning—0
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger—0
Bandwidth-efficient Inference for Neural Image Compression—0
Batch Normalization Alleviates the Spectral Bias in Coordinate Networks—0
Bi-Level Spatial and Channel-aware Transformer for Learned Image Compression—0
Binary Probability Model for Learning Based Image Compression—0
Bit Distribution Study and Implementation of Spatial Quality Map in the JPEG-AI Standardization—0
Bit Rate Matching Algorithm Optimization in JPEG-AI Verification Model—0
BlinQS: Blind Quality Scalable Image Compression Algorithm without using PCRD Optimization—0
Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms—0
Block-optimized Variable Bit Rate Neural Image Compression—0
Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images—0
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression—0
C2G-Net: Exploiting Morphological Properties for Image Classification—0
CALLIC: Content Adaptive Learning for Lossless Image Compression—0
Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net—0
Cascade Decoders-Based Autoencoders for Image Reconstruction—0
CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression—0
CBANet: Towards Complexity and Bitrate Adaptive Deep Image Compression using a Single Network—0
Channel-wise Feature Decorrelation for Enhanced Learned Image Compression—0
CIC: Circular Image Compression—0
Clustering-Based Quantisation for PDE-Based Image Compression—0
CMamba: Learned Image Compression with State Space Models—0
Coding Standards as Anchors for the CVPR CLIC video track—0
Color Learning for Image Compression—0
Combined Approach for Image Segmentation—0
Combining Progressive Image Compression and Random Access in DNA Data Storage—0
Bridging Compressed Image Latents and Multimodal Large Language Models—0
Compact Latent Representation for Image Compression (CLRIC)—0
Comparison of Lossless Image Formats—0
COMPASS: High-Efficiency Deep Image Compression with Arbitrary-scale Spatial Scalability—0
Compressed image quality assessment using stacking—0
Compressed sensing of astronomical images:orthogonal wavelets domains—0
Compressible and Searchable: AI-native Multi-Modal Retrieval System with Learned Image Compression—0
Compressing high-resolution data through latent representation encoding for downscaling large-scale AI weather forecast model—0
Compressing Weight-updates for Image Artifacts Removal Neural Networks—0
Compression-Resistant Backdoor Attack against Deep Neural Networks—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