Image Super-Resolution

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

69 leaderboard tables shown for this task, 69 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 69 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

43 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 43 until expanded.

Subtasks archive 2025-07-28

5 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 783 papers with code (1,589 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.

• Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
  15 Sep 2016 140 repositories listed Syntology ran 16 of 72 samples · 56 unverified · 11 pointer-only (licence)
  The adversarial loss pushes our solution to the natural image manifold using a discriminator network that is trained to differentiate between the super-resolved images and original photo-realistic images.
• Perceptual Losses for Real-Time Style Transfer and Super-Resolution
  27 Mar 2016 80 repositories listed Syntology ran 13 of 46 samples · 33 unverified · 5 pointer-only (licence)
  We consider image transformation problems, where an input image is transformed into an output image.
• Image Super-Resolution Using Deep Convolutional Networks
  31 Dec 2014 60 repositories listed Syntology ran 7 of 27 samples · 20 unverified · 7 pointer-only (licence)
  We further show that traditional sparse-coding-based SR methods can also be viewed as a deep convolutional network.
• SinGAN: Learning a Generative Model from a Single Natural Image
  2 May 2019 47 repositories listed Syntology ran 2 of 11 samples · 9 unverified · 3 pointer-only (licence)
  We introduce SinGAN, an unconditional generative model that can be learned from a single natural image.
• Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
  16 Sep 2016 47 repositories listed Syntology ran 4 of 20 samples · 16 unverified · 1 pointer-only (licence)
  This means that the super-resolution (SR) operation is performed in HR space.
• ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
  1 Sep 2018 46 repositories listed Syntology ran 8 of 44 samples · 36 unverified
  To further enhance the visual quality, we thoroughly study three key components of SRGAN - network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN).
• Enhanced Deep Residual Networks for Single Image Super-Resolution
  10 Jul 2017 45 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 2 pointer-only (licence)
  Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN).
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
  13 Aug 2016 22 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  Discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance.
• Image Super-Resolution Using Very Deep Residual Channel Attention Networks
  8 Jul 2018 20 repositories listed Syntology ran 10 of 22 samples · 12 unverified · 3 pointer-only (licence)
  To solve these problems, we propose the very deep residual channel attention networks (RCAN).
• PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
  8 Mar 2020 16 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We present an algorithm addressing this problem, PULSE (Photo Upsampling via Latent Space Exploration), which generates high-resolution, realistic images at resolutions previously unseen in the literature.
• Deep Back-Projection Networks For Super-Resolution
  7 Mar 2018 16 repositories listed Syntology ran 6 of 14 samples · 8 unverified
  The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output.
• Residual Dense Network for Image Super-Resolution
  24 Feb 2018 16 repositories listed Syntology ran 7 of 24 samples · 17 unverified · 1 pointer-only (licence)
  In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR.
• Accelerating the Super-Resolution Convolutional Neural Network
  1 Aug 2016 16 repositories listed Syntology ran 0 of 15 samples · 15 unverified
  As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) has demonstrated superior performance to the previous hand-crafted models either in speed and…
• Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
  23 Nov 2018 13 repositories listed Syntology ran 2 of 25 samples · 23 unverified
  Additionally, we propose a first set of metrics to quantitatively evaluate the accuracy as well as the perceptual quality of the temporal evolution.
• Wide Activation for Efficient and Accurate Image Super-Resolution
  27 Aug 2018 12 repositories listed Syntology ran 0 of 17 samples · 17 unverified · 2 pointer-only (licence)
  Keras-based implementation of WDSR, EDSR and SRGAN for single image super-resolution
• Invertible Image Rescaling
  12 May 2020 11 repositories listed Syntology ran 3 of 17 samples · 14 unverified
  High-resolution digital images are usually downscaled to fit various display screens or save the cost of storage and bandwidth, meanwhile the post-upscaling is adpoted to recover the original resolutions or the details…
• SwinIR: Image Restoration Using Swin Transformer
  23 Aug 2021 9 repositories listed Syntology ran 30 of 45 samples · 15 unverified · 5 pointer-only (licence)
  In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.
• Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
  25 May 2021 9 repositories listed Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
  Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead, significantly restricts their…
• SRFlow: Learning the Super-Resolution Space with Normalizing Flow
  25 Jun 2020 8 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  SRFlow therefore directly accounts for the ill-posed nature of the problem, and learns to predict diverse photo-realistic high-resolution images.
• The 2018 PIRM Challenge on Perceptual Image Super-resolution
  20 Sep 2018 8 repositories listed
  This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018.
• Accurate Image Super-Resolution Using Very Deep Convolutional Networks
  14 Nov 2015 8 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  We present a highly accurate single-image super-resolution (SR) method.
• Deep Back-Projection Networks for Single Image Super-resolution
  4 Apr 2019 7 repositories listed
  Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output.
• Recurrent Back-Projection Network for Video Super-Resolution
  25 Mar 2019 7 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We proposed a novel architecture for the problem of video super-resolution.
• "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.
• Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks
  4 Oct 2017 7 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)
  However, existing methods often require a large number of network parameters and entail heavy computational loads at runtime for generating high-accuracy super-resolution results.
• Revisiting RCAN: Improved Training for Image Super-Resolution
  27 Jan 2022 6 repositories listed
  Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight.
• Pre-Trained Image Processing Transformer
  1 Dec 2020 6 repositories listed
  To maximally excavate the capability of transformer, we present to utilize the well-known ImageNet benchmark for generating a large amount of corrupted image pairs.
• A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference
  8 Jan 2019 6 repositories listed Syntology ran 4 of 14 samples · 10 unverified · 1 pointer-only (licence)
  In this paper, Bayesian Convolutional Neural Network (BayesCNN) using Variational Inference is proposed, that introduces probability distribution over the weights.
• A Fully Progressive Approach to Single-Image Super-Resolution
  9 Apr 2018 6 repositories listed
  Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality.
• Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration
  22 Sep 2022 5 repositories listed
  Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data.

Syntology lines on 23 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.