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 651–700 of 1008 papers

TitleStatusHype
SG-JND: Semantic-Guided Just Noticeable Distortion Predictor For Image Compression—0
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication—0
SigVIC: Spatial Importance Guided Variable-Rate Image Compression—0
Simultaneously Learning Architectures and Features of Deep Neural Networks—0
SINCO: A Novel structural regularizer for image compression using implicit neural representations—0
Singular Value Decomposition of Images from Scanned Photographic Plates—0
LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression—0
Soft Compression for Lossless Image Coding—0
Soft then Hard: Rethinking the Quantization in Neural Image Compression—0
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations—0
Sparse Multi-layer Image Approximation: Facial Image Compression—0
Sparse Point Clouds Assisted Learned Image Compression—0
Spatially adaptive image compression using a tiled deep network—0
Spatially-Adaptive Learning-Based Image Compression with Hierarchical Multi-Scale Latent Spaces—0
SPC-NeRF: Spatial Predictive Compression for Voxel Based Radiance Field—0
Split Hierarchical Variational Compression—0
Stable Diffusion is a Natural Cross-Modal Decoder for Layered AI-generated Image Compression—0
STanH : Parametric Quantization for Variable Rate Learned Image Compression—0
Stereo Image Coding for Machines with Joint Visual Feature Compression—0
Stereo on a budget—0
Strategies in JPEG compression using Convolutional Neural Network (CNN)—0
Streaming Neural Images—0
Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Neural Network Algorithm—0
STW and SPIHT Wavelet compression using MATLAB wavelet Tool for Color Image—0
Substitutional Neural Image Compression—0
Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization—0
Target-Quality Image Compression with Recurrent, Convolutional Neural Networks—0
Task-Aware Quantization Network for JPEG Image Compression—0
Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference—0
Technical description of the EPFL submission to the JPEG DNA CfP—0
Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs—0
Test-time adaptation for image compression with distribution regularization—0
Test-Time Fine-Tuning of Image Compression Models for Multi-Task Adaptability—0
TFIC: End-to-End Text-Focused Image Compression for Coding for Machines—0
The Cyborg Astrobiologist: Matching of Prior Textures by Image Compression for Geological Mapping and Novelty Detection—0
The Effect of Lossy Compression on 3D Medical Images Segmentation with Deep Learning—0
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples—0
The Rate-Distortion-Perception-Classification Tradeoff: Joint Source Coding and Modulation via Inverse-Domain GANs—0
The Rate-Distortion-Perception Trade-off: The Role of Private Randomness—0
Thousand to One: Semantic Prior Modeling for Conceptual Coding—0
TinyLIC-High efficiency lossy image compression method—0
TokBench: Evaluating Your Visual Tokenizer before Visual Generation—0
Toward Joint Image Generation and Compression using Generative Adversarial Networks—0
Towards Analysis-friendly Face Representation with Scalable Feature and Texture Compression—0
Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach—0
Towards Dynamic Fault Tolerance for Hardware-Implemented Artificial Neural Networks: A Deep Learning Approach—0
Towards Facial Image Compression with Consistency Preserving Diffusion Prior—0
Towards High-fidelity Artistic Image Vectorization via Texture-Encapsulated Shape Parameterization—0
Towards Reproducible Learning-based Compression—0
Towards Robust Neural Image Compression: Adversarial Attack and Model Finetuning—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