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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–700 of 1008 papers

TitleStatusHype
Two-layer Near-lossless HDR Coding with Backward Compatibility to JPEG—0
UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding—0
UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks—0
Ultra High Fidelity Image Compression with _-constrained Encoding and Deep Decoding—0
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion—0
UniCompress: Enhancing Multi-Data Medical Image Compression with Knowledge Distillation—0
Unified learning-based lossy and lossless JPEG recompression—0
Union is strength in lossy image compression—0
Universal Efficient Variable-rate Neural Image Compression—0
Universal End-to-End Neural Network for Lossy Image Compression—0
Universal Learned Image Compression With Low Computational Cost—0
Universal Representations for Classification-enhanced Lossy Compression—0
Upsampling Improvement for Overfitted Neural Coding—0
Using Image Transformations to Learn Network Structure—0
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding—0
Variable Rate Deep Image Compression With a Conditional Autoencoder—0
Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets—0
Variable Rate Video Compression using a Hybrid Recurrent Convolutional Learning Framework—0
Variable-size Symmetry-based Graph Fourier Transforms for image compression—0
Vector Quantization using the Improved Differential Evolution Algorithm for Image Compression—0
Versatile Volumetric Medical Image Coding for Human-Machine Vision—0
Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics—0
Virtual Codec Supervised Re-Sampling Network for Image Compression—0
Vision Transformer-based Semantic Communications With Importance-Aware Quantization—0
Visually Similar Products Retrieval for Shopsy—0
V-variable image compression—0
VVC+M: Plug and Play Scalable Image Coding for Humans and Machines—0
Wavelet Feature Maps Compression for Low Bandwidth Convolutional Neural Networks—0
Why Accuracy Is Not Enough: The Need for Consistency in Object Detection—0
Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields—0
Window-based Channel Attention for Wavelet-enhanced Learned Image Compression—0
Wireless Image Retrieval at the Edge—0
XAI based Performance Preserving Adaptive Image Compression for Efficient Satellite Communication—0
X-GANs: Image Reconstruction Made Easy for Extreme Cases—0
X-Ray Image Compression Using Convolutional Recurrent Neural Networks—0
You Only Train Once: Loss-Conditional Training of Deep Networks—0
Your Demands Deserve More Bits: Referring Semantic Image Compression at Ultra-low Bitrate—0
STanH : Parametric Quantization for Variable Rate Learned Image Compression—0
Deep AutoEncoder-based Lossy Geometry Compression for Point Clouds—0
Generative Imaging and Image Processing via Generative Encoder—0
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis?—0
Human Synthesis and Scene Compositing—0
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization—0
3-D Context Entropy Model for Improved Practical Image Compression—0
4-D Epanechnikov Mixture Regression in Light Field Image Compression—0
A^2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems—0
A3D: Adaptive, Accurate, and Autonomous Navigation for Edge-Assisted Drones—0
A bi-level view of inpainting - based image compression—0
A Canonical Image Set for Examining and Comparing Image Processing Algorithms—0
Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture—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