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 901–950 of 1008 papers

TitleStatusHype
Virtual Codec Supervised Re-Sampling Network for Image Compression—0
Design an Advance computer-aided tool for Image Authentication and Classification—0
DSSLIC: Deep Semantic Segmentation-based Layered Image CompressionCode0
DMCNN: Dual-Domain Multi-Scale Convolutional Neural Network for Compression Artifacts Removal—0
Deep Image Compression via End-to-End LearningCode0
“Zero-Shot” Super-Resolution Using Deep Internal Learning—0
Autoencoders with Variable Sized Latent Vector for Image Compression—0
Image-Dependent Local Entropy Models for Learned Image Compression—0
CocoNet: A deep neural network for mapping pixel coordinates to color valuesCode0
Image Distortion Detection using Convolutional Neural Network—0
Block-optimized Variable Bit Rate Neural Image Compression—0
BlockCNN: A Deep Network for Artifact Removal and Image CompressionCode0
Deep Generative Models for Distribution-Preserving Lossy CompressionCode0
Image Restoration by Estimating Frequency Distribution of Local Patches—0
Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms—0
Neural Multi-scale Image Compression—0
A Canonical Image Set for Examining and Comparing Image Processing Algorithms—0
Deep Convolutional AutoEncoder-based Lossy Image CompressionCode0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Deformation Aware Image Compression—0
Generative Adversarial Networks for Extreme Learned Image CompressionCode0
One-Two-One Networks for Compression Artifacts Reduction in Remote Sensing—0
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples—0
Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data—0
Towards Image Understanding from Deep Compression without DecodingCode0
Learned Neural Iterative Decoding for Lossy Image Compression Systems—0
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial ExamplesCode0
DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework—0
Autoencoder based image compression: can the learning be quantization independent?—0
Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background—0
Lossless Image Compression Algorithm for Wireless Capsule Endoscopy by Content-Based Classification of Image Blocks—0
Spatially adaptive image compression using a tiled deep network—0
Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks—0
DeepSIC: Deep Semantic Image Compression—0
Multiple Description Convolutional Neural Networks for Image Compression—0
Near-lossless _-constrained Image Decompression via Deep Neural Network—0
Graph Spectral Image Processing—0
Enlarging Context with Low Cost: Efficient Arithmetic Coding with Trimmed Convolution—0
Conditional Probability Models for Deep Image CompressionCode0
Mosaicked multispectral image compression based on inter- and intra-band correlation—0
"Zero-Shot" Super-Resolution using Deep Internal LearningCode0
Learning a Virtual Codec Based on Deep Convolutional Neural Network to Compress Image—0
Deep Sampling Networks—0
Fractal image compression using upper bound on scaling parameterCode0
Image Compression: Sparse Coding vs. Bottleneck Autoencoders—0
Vector Quantization using the Improved Differential Evolution Algorithm for Image Compression—0
FPGA based Parallelized Architecture of Efficient Graph based Image Segmentation Algorithm—0
Constrained Convolutional Sparse Coding for Parametric Based Reconstruction of Line Drawings—0
Learning to Inpaint for Image Compression—0
Optimized Structured Sparse Sensing Matrices for Compressive Sensing—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