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Multi-scale Residual Network for Image Super-Resolution

https://doi.org/10.1007/978-3-030-01237-3_32

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-10593-2_13openalex-snapshot

Learning a Deep Convolutional Network for Image Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-319-16817-3_8openalex-snapshot

A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-319-46475-6_25openalex-snapshot

Accelerating the Super-Resolution Convolutional Neural Network

inferredcites →https://doi.org/10.1007/978-3-642-27413-8_47openalex-snapshot

On Single Image Scale-Up Using Sparse-Representations

inferredcites →https://doi.org/10.1007/s11042-016-4020-zopenalex-snapshot

Sketch-based manga retrieval using manga109 dataset

inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot

ImageNet Large Scale Visual Recognition Challenge

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/cvpr.2015.7299156openalex-snapshot

Single image super-resolution from transformed self-exemplars

inferredcites →https://doi.org/10.1109/cvpr.2016.181openalex-snapshot

Deeply-Recursive Convolutional Network for Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2016.182openalex-snapshot

Accurate Image Super-Resolution Using Very Deep Convolutional Networks

inferredcites →https://doi.org/10.1109/cvpr.2016.207openalex-snapshot

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.19openalex-snapshot

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot

Densely Connected Convolutional Networks

inferredcites →https://doi.org/10.1109/cvpr.2017.298openalex-snapshot

Image Super-Resolution via Deep Recursive Residual Network

inferredcites →https://doi.org/10.1109/cvpr.2017.618openalex-snapshot

Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution

inferredcites →https://doi.org/10.1109/cvprw.2017.150openalex-snapshot

NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study

inferredcites →https://doi.org/10.1109/cvprw.2017.151openalex-snapshot

Enhanced Deep Residual Networks for Single Image Super-Resolution

inferredcites →https://doi.org/10.1109/iccv.2001.937655openalex-snapshot

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot

Image quality assessment: from error visibility to structural similarity

inferredcites →https://doi.org/10.1109/tip.2010.2050625openalex-snapshot

Image Super-Resolution Via Sparse Representation

inferredcites →https://doi.org/10.1109/tpami.2010.161openalex-snapshot

Contour Detection and Hierarchical Image Segmentation

inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.5244/c.26.135openalex-snapshot

Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A Two-Stage Multi-Scale Attention Network for Single Image Super-Resolution

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Multi-scale Information Distillation Network for Image Super Resolution in NSCT Domain

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Dual-Path Recurrent Network for Image Super-Resolution

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Effective Utilization of Hybrid Residual Modules in Deep Neural Networks for Super Resolution

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LiteHandNet: A Lightweight Hand Pose Estimation Network via Structural Feature Enhancement

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Single Image Super-Resolution with Sequential Multi-axis Blocked Attention

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Image Restoration for Beautification

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MetaVSR: A Novel Approach to Video Super-Resolution for Arbitrary Magnification

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Adjust Your Focus: Defocus Deblurring from Dual-Pixel Images Using Explicit Multi-Scale Cross-Correlation

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Adversarial Training for Boosting Super-Resolution by Combination with License Plate Recognition

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Image Super-Resolution with Multi-scale Hybrid Attention

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Compressed Depth Map Super-Resolution and Restoration: AIM 2024 Challenge Results

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Single-Image Super-Resolution by Self-supervised Consistent Representation Learning

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Computationally Efficient Super-Resolution Approach for Real-World Images

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Comprehensive Survey on Context-Based Learning in Video Super-Resolution

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Adaptive Multi-scale Fusion Transformer for Image Super-Resolution

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Deep Learning for Super-Resolution Imaging

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Lesion-Focused Ultrasound Images Super-Resolution Reconstruction Based on Coarse-to-Fine Diffusion Model

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Hierarchical Directional Attention Fusion Network for Image Super Resolution

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An Integrated Deep Learning Model for Enhancing Image Quality

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Second-Order Gradient Loss Guided Single-Image Super-Resolution

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MFAAnet: New Feature Extraction Network in Image Super-Resolution

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Deep Convolutional Neural Network with Bicubic Interpolation for Super-Resolution in Low-Resolution Images

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No-reference image quality assessment with multi-scale weighted residuals and channel attention mechanism

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Multi-scale lightweight transformer-style hybrid distillation network for image super-resolution

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Progressive residual networks for image super-resolution

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Multi-scale fractal residual network for image super-resolution

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Multi-scale feature aggregation network for Image super-resolution

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Dual-attention guided multi-scale network for single image super-resolution

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Multi-scale convolution networks for seismic event classification with windowed self-attention

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Improved edge-guided network for single image super-resolution

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Lightweight adaptive enhanced attention network for image super-resolution

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Super resolution reconstruction of CT images based on multi-scale attention mechanism

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Enhanced multi-scale feature progressive network for image Deblurring

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A Review of Single Image Super Resolution Techniques using Convolutional Neural Networks

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U-SRN: Convolutional Neural network for single image super resolution

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Lightweight improved residual network for efficient inverse tone mapping

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Intermediate-term memory mechanism inspired lightweight single image super resolution

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A novel multimodal deep learning architecture integrating a multi-scale gated residual block and soft attention for skin lesion classification

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Pixel-Level and Perceptual-Level Regularized Adversarial Learning for Joint Motion Deblurring and Super-Resolution

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Super-Resolution Reconstruction of Single Image Combining Bionic Eagle-Eye and Multi-scale

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Pre-denoising 3D Multi-scale Fusion Attention Network for Low-Light Enhancement

inferred← citeshttps://doi.org/10.1007/s11227-019-03066-3openalex-snapshot

Pulmonary nodule image super-resolution using multi-scale deep residual channel attention network with joint optimization

inferred← citeshttps://doi.org/10.1007/s11227-022-04617-xopenalex-snapshot

Remote sensing image reconstruction using an asymmetric multi-scale super-resolution network

inferred← citeshttps://doi.org/10.1007/s11227-024-06569-wopenalex-snapshot

A dual-path feature reuse multi-scale network for remote sensing image super-resolution

inferred← citeshttps://doi.org/10.1007/s11227-025-07659-zopenalex-snapshot

CVSR: complex-valued networks for video super-resolution

inferred← citeshttps://doi.org/10.1007/s11263-021-01545-wopenalex-snapshot

CODON: On Orchestrating Cross-Domain Attentions for Depth Super-Resolution

inferred← citeshttps://doi.org/10.1007/s11276-023-03611-2openalex-snapshot

A hyperspectral pansharpening method using retrain transformer network for remote sensing images in UAV communications system

inferred← citeshttps://doi.org/10.1007/s11554-021-01142-7openalex-snapshot

A lightweight multi-scale feature integration network for real-time single image super-resolution

inferred← citeshttps://doi.org/10.1007/s11554-021-01150-7openalex-snapshot

Single-image super-resolution based on multi-branch residual pyramid network

inferred← citeshttps://doi.org/10.1007/s11554-025-01663-5openalex-snapshot

Dilated-convolutional feature modulation network for efficient image super-resolution

inferred← citeshttps://doi.org/10.1007/s11704-023-2588-9openalex-snapshot

Single image super-resolution: a comprehensive review and recent insight

inferred← citeshttps://doi.org/10.1007/s11760-021-02011-3openalex-snapshot

Stratified attention dense network for image super-resolution

inferred← citeshttps://doi.org/10.1007/s11760-021-02030-0openalex-snapshot

Multiscale U-net-based accelerated magnetic resonance imaging reconstruction

inferred← citeshttps://doi.org/10.1007/s11760-021-02038-6openalex-snapshot

Single-image super-resolution via selective multi-scale network

inferred← citeshttps://doi.org/10.1007/s11760-021-02095-xopenalex-snapshot

Attention-enhanced multi-scale residual network for single image super-resolution

inferred← citeshttps://doi.org/10.1007/s11760-022-02136-zopenalex-snapshot

A lightweight multi-scale residual network for single image super-resolution

inferred← citeshttps://doi.org/10.1007/s11760-022-02421-xopenalex-snapshot

Thermal image super-resolution via multi-path residual attention network

inferred← citeshttps://doi.org/10.1007/s11760-023-02797-4openalex-snapshot

MMFF-NET: Multi-layer and multi-scale feature fusion network for low-light infrared image enhancement

inferred← citeshttps://doi.org/10.1007/s11760-024-03127-yopenalex-snapshot

FRR-NET: a fast reparameterized residual network for low-light image enhancement

inferred← citeshttps://doi.org/10.1007/s11760-025-03857-7openalex-snapshot

Rock core micrograph image super-resolution reconstruction using a novel deep residual network

inferred← citeshttps://doi.org/10.1007/s11760-025-04185-6openalex-snapshot

Super-Resolution Image Reconstruction based on Random-coupled Neural Network and EDSR

inferred← citeshttps://doi.org/10.1007/s11760-025-04255-9openalex-snapshot

Multi-scale feedback residual network for image super-resolution

inferred← citeshttps://doi.org/10.1007/s11760-025-04466-0openalex-snapshot

Multi-scale attention network with dynamic offset sampling for image super-resolution

inferred← citeshttps://doi.org/10.1007/s11760-026-05138-3openalex-snapshot

AREN: An Efficient Image Super-Resolution Net with Adaptive Resolution Enhancment Modulation

inferred← citeshttps://doi.org/10.1007/s12065-025-01135-6openalex-snapshot

Deep learning based hyperspectral band selection using position-sensitive axial attention mechanism

inferred← citeshttps://doi.org/10.1007/s12559-024-10293-1openalex-snapshot

Multi-resolution Twinned Residual Auto-Encoders (MR-TRAE)—A Novel DL Model for Image Multi-resolution

inferred← citeshttps://doi.org/10.1007/s13042-023-01773-1openalex-snapshot

Two-channel deep recursive multi-scale network based on multi-attention for no-reference image quality assessment

inferred← citeshttps://doi.org/10.1007/s13042-023-01928-0openalex-snapshot

TFEN: two-stage feature enhancement network for single-image super-resolution

inferred← citeshttps://doi.org/10.1007/s13042-024-02138-yopenalex-snapshot

TARN: a lightweight two-branch adaptive residual network for image super-resolution

inferred← citeshttps://doi.org/10.1007/s13369-021-06145-xopenalex-snapshot

Image Super-Resolution Based on Generalized Residual Network

inferred← citeshttps://doi.org/10.1007/s13369-024-09876-9openalex-snapshot

Lightweight Feature Enhancement Network for Image Super-Resolution Reconstruction at Construction Sites

inferred← citeshttps://doi.org/10.1007/s40747-020-00205-9openalex-snapshot

An improved simulated annealing algorithm based on residual network for permutation flow shop scheduling

inferred← citeshttps://doi.org/10.1007/s40747-024-01724-5openalex-snapshot

TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis

inferred← citeshttps://doi.org/10.1007/s40747-024-01760-1openalex-snapshot

XTNSR: Xception-based transformer network for single image super resolution

inferred← citeshttps://doi.org/10.1007/s40747-026-02245-zopenalex-snapshot

FATSNet: transformer-based skip network with frequency attention for remote sensing image super-resolution

inferred← citeshttps://doi.org/10.1007/s42600-025-00434-2openalex-snapshot

SEMS-DRNet: Attention enhanced multi-scale residual blocks with Bayesian optimization for diabetic retinopathy classification

inferred← citeshttps://doi.org/10.1007/s44443-025-00109-zopenalex-snapshot

MWFNet: A multi-level wavelet fusion network for hippocampal subfield segmentation

inferred← citeshttps://doi.org/10.1007/s44443-025-00214-zopenalex-snapshot

Hourglass attention for image super-resolution

inferred← citeshttps://doi.org/10.1007/s44443-025-00363-1openalex-snapshot

Soft pattern coding transformer for lightweight image super resolution

inferred← citeshttps://doi.org/10.1016/j.acags.2023.100143openalex-snapshot

A comparative analysis of super-resolution techniques for enhancing micro-CT images of carbonate rocks

inferred← citeshttps://doi.org/10.1016/j.asej.2024.102861openalex-snapshot

Densely integrated multi-branch attentive net for image dehazing

inferred← citeshttps://doi.org/10.1016/j.asoc.2024.112569openalex-snapshot

Single image super-resolution with lightweight multi-scale dilated attention network

inferred← citeshttps://doi.org/10.1016/j.bspc.2025.107828openalex-snapshot

Narrowing the regional attention imbalance in medical image segmentation via feature decorrelation

inferred← citeshttps://doi.org/10.1016/j.bspc.2025.108126openalex-snapshot

Multi-scale feature adaptive aggregation Transformer for super-resolution of lung computed tomography images

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.109928openalex-snapshot

DPDN-Dual Path Degradation Network for prostate MRI blind super-resolution

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.110198openalex-snapshot

Reference-based DWI super-resolution network using dual split factor attention and progressive feature matching

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.110584openalex-snapshot

Co-Retention feature pyramid network for low-dose CT denoising via spatial and frequency domain learning

inferred← citeshttps://doi.org/10.1016/j.cag.2022.12.005openalex-snapshot

DGRN: Image super-resolution with dual gradient regression guidance

inferred← citeshttps://doi.org/10.1016/j.cag.2023.04.007openalex-snapshot

Image super-resolution with multi-scale fractal residual attention network

inferred← citeshttps://doi.org/10.1016/j.cma.2025.118356openalex-snapshot

Mixed-depth physics-informed neural network with nested activation mechanism in solving partial differential equations

inferred← citeshttps://doi.org/10.1016/j.cmpb.2021.106330openalex-snapshot

Residual dense network for medical magnetic resonance images super-resolution

inferred← citeshttps://doi.org/10.1016/j.compag.2023.108413openalex-snapshot

MFENet: Multi-scale feature extraction network for images deblurring and segmentation of swinging wolfberry branch

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2020.103873openalex-snapshot

Unsupervised smoke to desmoked laparoscopic surgery images using contrast driven Cyclic-DesmokeGAN

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110345openalex-snapshot

A general survey on medical image super-resolution via deep learning

inferred← citeshttps://doi.org/10.1016/j.compfluid.2025.106592openalex-snapshot

Dual scale Residual-Network for turbulent flow sub grid scale resolving: A prior analysis

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2024.102374openalex-snapshot

Deep local-to-global feature learning for medical image super-resolution

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103005openalex-snapshot

Learning lightweight Multi-Scale Feedback Residual network for single image super-resolution

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103007openalex-snapshot

Residual network with detail perception loss for single image super-resolution

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103029openalex-snapshot

Two-stream deep sparse network for accurate and efficient image restoration

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103034openalex-snapshot

Refining high-frequencies for sharper super-resolution and deblurring

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103038openalex-snapshot

E-ProSRNet: An enhanced progressive single image super-resolution approach

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103044openalex-snapshot

Learning deep edge prior for image denoising

inferred← citeshttps://doi.org/10.1016/j.cviu.2020.103075openalex-snapshot

Accurate MR image super-resolution via lightweight lateral inhibition network

inferred← citeshttps://doi.org/10.1016/j.cviu.2021.103202openalex-snapshot

Single image super-resolution via hybrid resolution NSST prediction

inferred← citeshttps://doi.org/10.1016/j.cviu.2021.103254openalex-snapshot

Lightweight adaptive weighted network for single image super-resolution

inferred← citeshttps://doi.org/10.1016/j.cviu.2023.103819openalex-snapshot

Snow Mask Guided Adaptive Residual Network for Image Snow Removal

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