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 601–650 of 1008 papers

TitleStatusHype
Does lossy image compression affect racial bias within face recognition?—0
A Unified Image Preprocessing Framework For Image Compression—0
Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training—0
Streaming-capable High-performance Architecture of Learned Image Compression CodecsCode0
Evaluating the Practicality of Learned Image Compression—0
Content-oriented learned image compression—0
Why Accuracy Is Not Enough: The Need for Consistency in Object Detection—0
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression—0
DCT Approximations Based on Chen's Factorization—0
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
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
A Novel Algorithm for Exact Concave Hull Extraction—0
Universal Learned Image Compression With Low Computational Cost—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
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
Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery—0
Dense residual Transformer for image denoising—0
Analysis of Neural Image Compression Networks for Machine-to-Machine Communication—0
An Efficient Architecture and High-Throughput Implementation of CCSDS-123.0-B-2 Hybrid Entropy Coder Targeting Space-Grade SRAM FPGA Technology—0
Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms—0
Joint Image Compression and Denoising via Latent-Space Scalability—0
Estimating the Resize Parameter in End-to-end Learned Image CompressionCode0
Identity Preserving Loss for Learned Image Compression—0
Neural Space-filling Curves—0
Feature Compression for Rate Constrained Object Detection on the Edge—0
Split Hierarchical Variational Compression—0
Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain—0
Image Compression and Actionable Intelligence With Deep Neural Networks—0
End-to-End Learned Block-Based Image Compression with Block-Level Masked Convolutions and Asymptotic Closed Loop Training—0
Image Storage on Synthetic DNA Using Autoencoders—0
SC2 Benchmark: Supervised Compression for Split Computing—0
aiWave: Volumetric Image Compression with 3-D Trained Affine Wavelet-like Transform—0
Improved Wavelets for Image Compression from Unitary Circuits—0
Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression—0
Transformations in Learned Image Compression from a Modulation Perspective—0
Hybrid Model-based / Data-driven Graph Transform for Image Coding—0
Post-Training Quantization for Cross-Platform Learned Image Compression—0
Reducing Redundancy in the Bottleneck Representation of the Autoencoders—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