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Multi-Grained Attention Networks for Single Image Super-Resolution

https://doi.org/10.1109/tcsvt.2020.2988895

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What this work says

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

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CBAM: Convolutional Block Attention Module

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Image Super-Resolution Using Very Deep Residual Channel Attention Networks

inferredcites →https://doi.org/10.1007/978-3-030-01237-3_32openalex-snapshot

Multi-scale Residual Network for Image Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-030-01261-8_31openalex-snapshot

Multi-scale Spatially-Asymmetric Recalibration for Image Classification

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

Accelerating the Super-Resolution Convolutional Neural Network

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On Single Image Scale-Up Using Sparse-Representations

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Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch

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Sketch-based manga retrieval using manga109 dataset

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One-two-one networks for compression artifacts reduction in remote sensing

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot

Deep learning

inferredcites →https://doi.org/10.1109/access.2018.2831791openalex-snapshot

High Resolution Similarity Directed Adjusted Anchored Neighborhood Regression for Single Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2012.6247791openalex-snapshot

Multi-scale dictionary for single image super-resolution

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

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Learning Deep CNN Denoiser Prior for Image Restoration

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Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution

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SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning

inferredcites →https://doi.org/10.1109/cvpr.2017.683openalex-snapshot

Residual Attention Network for Image Classification

inferredcites →https://doi.org/10.1109/cvpr.2018.00262openalex-snapshot

Residual Dense Network for Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2018.00344openalex-snapshot

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Occluded Pedestrian Detection Through Guided Attention in CNNs

inferredcites →https://doi.org/10.1109/cvprw.2017.149openalex-snapshot

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

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.2017.486openalex-snapshot

MemNet: A Persistent Memory Network for Image Restoration

inferredcites →https://doi.org/10.1109/iccv.2017.514openalex-snapshot

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inferredcites →https://doi.org/10.1109/icdar.2017.143openalex-snapshot

Attention-Based Extraction of Structured Information from Street View Imagery

inferredcites →https://doi.org/10.1109/icip.2017.8296427openalex-snapshot

Single image super-resolution with dilated convolution based multi-scale information learning inception module

inferredcites →https://doi.org/10.1109/icpr.2018.8546130openalex-snapshot

SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks

inferredcites →https://doi.org/10.1109/lgrs.2014.2360457openalex-snapshot

Compressed Sensing of a Remote Sensing Image Based on the Priors of the Reference Image

inferredcites →https://doi.org/10.1109/tcsvt.2018.2839879openalex-snapshot

Resolution-Aware Network for Image Super-Resolution

inferredcites →https://doi.org/10.1109/tcsvt.2018.2864777openalex-snapshot

Cascaded Deep Networks With Multiple Receptive Fields for Infrared Image Super-Resolution

inferredcites →https://doi.org/10.1109/tcsvt.2018.2883771openalex-snapshot

Fast Single-Image Super-Resolution via Deep Network With Component Learning

inferredcites →https://doi.org/10.1109/tcsvt.2018.2890271openalex-snapshot

Multi-Scale Frequency Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Network

inferredcites →https://doi.org/10.1109/tcsvt.2019.2915238openalex-snapshot

Channel-Wise and Spatial Feature Modulation Network for Single Image Super-Resolution

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.2012.2189576openalex-snapshot

Interpolation-Based Image Super-Resolution Using Multisurface Fitting

inferredcites →https://doi.org/10.1109/tip.2012.2208977openalex-snapshot

Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression

inferredcites →https://doi.org/10.1109/tip.2014.2305844openalex-snapshot

A Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution

inferredcites →https://doi.org/10.1109/tkde.2021.3130191openalex-snapshot

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

inferredcites →https://doi.org/10.1109/tmm.2016.2601020openalex-snapshot

SRLSP: A Face Image Super-Resolution Algorithm Using Smooth Regression With Local Structure Prior

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

Contour Detection and Hierarchical Image Segmentation

inferredcites →https://doi.org/10.1109/tpami.2015.2439281openalex-snapshot

Image Super-Resolution Using Deep Convolutional Networks

inferredcites →https://doi.org/10.1109/tpami.2019.2913372openalex-snapshot

Squeeze-and-Excitation Networks

inferredcites →https://doi.org/10.24963/ijcai.2018/227openalex-snapshot

Memory Attention Networks for Skeleton-based Action Recognition

inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot

AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)

inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-snapshot

Neural Machine Translation by Jointly Learning to Align and Translate

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

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.48550/arxiv.1502.03044openalex-snapshot

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

inferredcites →https://doi.org/10.48550/arxiv.1802.08808openalex-snapshot

Single Image Super-Resolution via Cascaded Multi-Scale Cross Network

inferredcites →https://doi.org/10.48550/arxiv.2001.06937openalex-snapshot

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

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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Joint Face Completion and Super-Resolution Using Multi-Scale Feature Relation Learning

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Hiren: Towards Higher Supervision Quality Forbetter Scene Text Image Super-Resolution

inferred← citeshttps://doi.org/10.1002/9781119752134.ch1openalex-snapshot

Single Image Super‐Resolution Using GANs for High‐Upscaling Factors

inferred← citeshttps://doi.org/10.1002/mp.16249openalex-snapshot

STEDNet: Swin transformer‐based encoder–decoder network for noise reduction in low‐dose CT

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Self-calibrated Attention Neural Network for Real-World Super Resolution

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Image Super-Resolution with Multi-scale Hybrid Attention

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SCCADC-SR: a real image super-resolution based on self-calibration convolution and adaptive dense connection

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Single image deraining using multi-scales context information and attention network

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Joint face completion and super-resolution using multi-scale feature relation learning

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DRGAN: A dual resolution guided low-resolution image inpainting

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Balanced Spatial Feature Distillation and Pyramid Attention Network for Lightweight Image Super-resolution

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HiREN: Towards higher supervision quality for better scene text image super-resolution

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CVANet: Cascaded visual attention network for single image super-resolution

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Color Polarization Image Super-Resolution Reconstruction via a Cross-Branch Supervised Learning Strategy

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SSIR: Spatial shuffle multi-head self-attention for Single Image Super-Resolution

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Generative adversarial network-based super-resolution reconstruction of remote sensing images

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Pyramidal dense attention networks for single image super‐resolution

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Progressive low/high-resolution Space Attention Fusion Network for Single Image Super-Resolution

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LPN-IDD: A Lightweight Pyramid Network for Image Deraining and Detection

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Multi-scale feature feedback network for single image super-resolution

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DeBeauty: A Joint Framework for Facial Beautification Removal Based on Spatial Collaborative Adaptation and Hyperplane Relocation

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