Image Compression

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

11 leaderboard tables shown for this task, 11 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 11 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

12 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

4 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 320 papers with code (1,008 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Variational image compression with a scale hyperprior
  1 Feb 2018 16 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  We describe an end-to-end trainable model for image compression based on variational autoencoders.
• End-to-end Optimized Image Compression
  5 Nov 2016 14 repositories listed Syntology ran 4 of 20 samples · 16 unverified · 4 pointer-only (licence)
  We describe an image compression method, consisting of a nonlinear analysis transformation, a uniform quantizer, and a nonlinear synthesis transformation.
• "Zero-Shot" Super-Resolution using Deep Internal Learning
  17 Dec 2017 7 repositories listed
  On such images, our method outperforms SotA CNN-based SR methods, as well as previous unsupervised SR methods.
• Full Resolution Image Compression with Recurrent Neural Networks
  18 Aug 2016 7 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the…
• QVRF: A Quantization-error-aware Variable Rate Framework for Learned Image Compression
  10 Mar 2023 6 repositories listed
  In this paper, we present a Quantization-error-aware Variable Rate Framework (QVRF) that utilizes a univariate quantization regulator a to achieve wide-range variable rates within a single model.
• ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding
  21 Mar 2022 6 repositories listed Syntology ran 8 of 12 samples · 4 unverified
  Recently, learned image compression techniques have achieved remarkable performance, even surpassing the best manually designed lossy image coders.
• An End-to-End Compression Framework Based on Convolutional Neural Networks
  2 Aug 2017 5 repositories listed
  The second CNN, named reconstruction convolutional neural network (RecCNN), is used to reconstruct the decoded image with high-quality in the decoding end.
• Checkerboard Context Model for Efficient Learned Image Compression
  29 Mar 2021 4 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  To the best of our knowledge, this is the first exploration on parallelization-friendly spatial context model for learned image compression.
• CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
  5 Nov 2020 4 repositories listed Syntology ran 6 of 6 samples · 0 unverified · 6 pointer-only (licence)
  This paper presents CompressAI, a platform that provides custom operations, layers, models and tools to research, develop and evaluate end-to-end image and video compression codecs.
• High-Fidelity Generative Image Compression
  17 Jun 2020 4 repositories listed
  We extensively study how to combine Generative Adversarial Networks and learned compression to obtain a state-of-the-art generative lossy compression system.
• Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules
  6 Jan 2020 4 repositories listed Syntology ran 0 of 14 samples · 14 unverified
  In this paper, we explore the remaining redundancy of recent learned compression algorithms.
• Practical Full Resolution Learned Lossless Image Compression
  30 Nov 2018 4 repositories listed
  We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000.
• Lossy Image Compression with Compressive Autoencoders
  1 Mar 2017 4 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We propose a new approach to the problem of optimizing autoencoders for lossy image compression.
• Learned Image Compression with Mixed Transformer-CNN Architectures
  27 Mar 2023 3 repositories listed Syntology ran 6 of 9 samples · 3 unverified
  Most existing LIC methods are Convolutional Neural Networks-based (CNN-based) or Transformer-based, which have different advantages.
• Transformer-based Transform Coding
  29 Sep 2021 3 repositories listed
  Neural data compression based on nonlinear transform coding has made great progress over the last few years, mainly due to improvements in prior models, quantization methods and nonlinear transforms.
• Neural Distributed Image Compression using Common Information
  22 Jun 2021 3 repositories listed
  The received latent representation and the locally generated common information are passed through a decoder network to obtain an enhanced reconstruction of the input image.
• M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection
  20 Apr 2021 3 repositories listed Syntology ran 4 of 11 samples · 7 unverified
  The widespread dissemination of Deepfakes demands effective approaches that can detect perceptually convincing forged images.
• Channel-wise Autoregressive Entropy Models for Learned Image Compression
  17 Jul 2020 3 repositories listed
  In learning-based approaches to image compression, codecs are developed by optimizing a computational model to minimize a rate-distortion objective.
• Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement
  4 Mar 2020 3 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  In our HLVC approach, the hierarchical quality benefits the coding efficiency, since the high quality information facilitates the compression and enhancement of low quality frames at encoder and decoder sides,…
• Deep Image Compression using Decoder Side Information
  14 Jan 2020 3 repositories listed
  We base our algorithm on the assumption that the image available to the encoder and the image available to the decoder are correlated, and we let the network learn these correlations in the training phase.
• Learning to compress and search visual data in large-scale systems
  24 Jan 2019 3 repositories listed
  The problem of high-dimensional and large-scale representation of visual data is addressed from an unsupervised learning perspective.
• Residual Dense Network for Image Restoration
  25 Dec 2018 3 repositories listed
  We fully exploit the hierarchical features from all the convolutional layers.
• Joint Autoregressive and Hierarchical Priors for Learned Image Compression
  8 Sep 2018 3 repositories listed
  While it is well known that autoregressive models come with a significant computational penalty, we find that in terms of compression performance, autoregressive and hierarchical priors are complementary and, together,…
• Efficient Nonlinear Transforms for Lossy Image Compression
  31 Jan 2018 3 repositories listed
  We assess the performance of two techniques in the context of nonlinear transform coding with artificial neural networks, Sadam and GDN.
• Semantic Perceptual Image Compression using Deep Convolution Networks
  27 Dec 2016 3 repositories listed
  Here, we present a powerful cnn tailored to the specific task of semantic image understanding to achieve higher visual quality in lossy compression.
• Privacy-Preserving Face Recognition Using Trainable Feature Subtraction
  19 Mar 2024 2 repositories listed
  Recognizable identity features within the image are encouraged by co-training a recognition model on its high-dimensional feature representation.
• Image Coding for Machines with Edge Information Learning Using Segment Anything
  7 Mar 2024 2 repositories listed
  Image Coding for Machines (ICM) is an image compression technique for image recognition.
• Region-Adaptive Transform with Segmentation Prior for Image Compression
  1 Mar 2024 2 repositories listed Syntology ran 14 of 18 samples · 4 unverified · 18 pointer-only (licence)
  However, there is no prior research on neural transform that focuses on specific regions.
• MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
  26 Feb 2024 2 repositories listed
  With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic.
• Compact 3D Scene Representation via Self-Organizing Gaussian Grids
  19 Dec 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we introduce a compact scene representation organizing the parameters of 3D Gaussian Splatting (3DGS) into a 2D grid with local homogeneity, ensuring a drastic reduction in storage requirements without…

Syntology lines on 13 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.