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 251–300 of 1008 papers

TitleStatusHype
FOOL: Addressing the Downlink Bottleneck in Satellite Computing with Neural Feature CompressionCode1
Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis—0
S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention ContextCode1
Powerful Lossy Compression for Noisy Images—0
Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization—0
Privacy-Preserving Face Recognition Using Trainable Feature SubtractionCode0
Overfitted image coding at reduced complexityCode0
Channel-wise Feature Decorrelation for Enhanced Learned Image Compression—0
Process-and-Forward: Deep Joint Source-Channel Coding Over Cooperative Relay NetworksCode1
Noise Dimension of GAN: An Image Compression Perspective—0
CAMSIC: Content-aware Masked Image Modeling Transformer for Stereo Image CompressionCode1
Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression—0
Probing Image Compression For Class-Incremental Learning—0
Image Coding for Machines with Edge Information Learning Using Segment AnythingCode1
Enhancing the Rate-Distortion-Perception Flexibility of Learned Image Codecs with Conditional Diffusion Decoders—0
Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual FidelityCode1
Neural Network Assisted Lifting Steps For Improved Fully Scalable Lossy Image Compression in JPEG 2000Code0
Region-Adaptive Transform with Segmentation Prior for Image CompressionCode1
Towards Backward-Compatible Continual Learning of Image CompressionCode0
Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction OffsetsCode0
Exploration of Learned Lifting-Based Transform Structures for Fully Scalable and Accessible Wavelet-Like Image Compression—0
Bit Rate Matching Algorithm Optimization in JPEG-AI Verification Model—0
Bit Distribution Study and Implementation of Spatial Quality Map in the JPEG-AI Standardization—0
Distortion-Controlled Dithering with Reduced Recompression Rate—0
SPC-NeRF: Spatial Predictive Compression for Voxel Based Radiance Field—0
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal ModelCode1
Traditional Transformation Theory Guided Model for Learned Image Compression—0
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel—0
Transformer-based Learned Image Compression for Joint Decoding and Denoising—0
3D Point Cloud Compression with Recurrent Neural Network and Image Compression MethodsCode2
TinyLIC-High efficiency lossy image compression method—0
Extreme Video Compression with Pre-trained Diffusion ModelsCode2
Saliency-aware End-to-end Learned Variable-Bitrate 360-degree Image Compression—0
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing DiffusionCode0
Learned Image Compression with Text Quality Enhancement—0
Joint End-to-End Image Compression and Denoising: Leveraging Contrastive Learning and Multi-Scale Self-ONNs—0
RAGE for the Machine: Image Compression with Low-Cost Random Access for Embedded Applications—0
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language ModelsCode2
Perceptual Learned Image Compression via End-to-End JND-Based Optimization—0
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)Code0
UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding—0
Compressed image quality assessment using stacking—0
Robustly overfitting latents for flexible neural image compression—0
Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression—0
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution—0
FLLIC: Functionally Lossless Image Compression—0
An Efficient Implicit Neural Representation Image Codec Based on Mixed Autoregressive Model for Low-Complexity Decoding—0
A Training-Free Defense Framework for Robust Learned Image Compression—0
Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding—0
Attack and Defense Analysis of Learned Image Compression—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