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
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
Content-oriented learned image compression—0
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression—0
DCT Approximations Based on Chen's Factorization—0
Optimizing Image Compression via Joint Learning with DenoisingCode1
XAI based Performance Preserving Adaptive Image Compression for Efficient Satellite Communication—0
Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City ApplicationsCode0
Neural Distributed Image Compression with Cross-Attention Feature AlignmentCode1
Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture—0
Forward Error Correction applied to JPEG-XS codestreams—0
Efficient Pruning for Machine Learning Under Homomorphic Encryption—0
Flexible-Rate Learned Hierarchical Bi-Directional Video Compression With Motion Refinement and Frame-Level Bit AllocationCode1
Universal Learned Image Compression With Low Computational Cost—0
A Novel Algorithm for Exact Concave Hull Extraction—0
Asymmetric Learned Image Compression with Multi-Scale Residual Block, Importance Map, and Post-Quantization Filtering—0
Memory-Efficient Learned Image Compression with Pruned Hyperprior Module—0
Preprocessing Enhanced Image Compression for Machine Vision—0
Perceptual Quality Assessment for Fine-Grained Compressed Images—0
Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?—0
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding—0
Low-complexity Three-dimensional Discrete Hartley Transform Approximations for Medical Image Compression—0
Q-LIC: Quantizing Learned Image Compression with Channel Splitting—0
PO-ELIC: Perception-Oriented Efficient Learned Image CodingCode1
MALICE: Manipulation Attacks on Learned Image ComprEssion—0
Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net—0
Enhancing VVC with Deep Learning based Multi-Frame Post-Processing—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