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Memory-Augmented Non-Local Attention for Video Super-Resolution

https://doi.org/10.1109/cvpr52688.2022.01731

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01234-2_18openalex-snapshot

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

inferredcites →https://doi.org/10.1007/978-3-030-11021-5_5openalex-snapshot

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

inferredcites →https://doi.org/10.1007/978-3-030-58517-4_31openalex-snapshot

Learning Joint Spatial-Temporal Transformations for Video Inpainting

inferredcites →https://doi.org/10.1007/978-3-030-58580-8_19openalex-snapshot

Memory-Augmented Dense Predictive Coding for Video Representation Learning

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/s11263-018-01144-2openalex-snapshot

Video Enhancement with Task-Oriented Flow

inferredcites →https://doi.org/10.1109/cvpr.2008.4587647openalex-snapshot

Image super-resolution as sparse representation of raw image patches

inferredcites →https://doi.org/10.1109/cvpr.2008.4587659openalex-snapshot

Image super-resolution using gradient profile prior

inferredcites →https://doi.org/10.1109/cvpr.2013.141openalex-snapshot

Fast Image Super-Resolution Based on In-Place Example Regression

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.2017.19openalex-snapshot

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

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.2017.304openalex-snapshot

Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation

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/cvpr.2018.00068openalex-snapshot

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

inferredcites →https://doi.org/10.1109/cvpr.2018.00070openalex-snapshot

Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform

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

Residual Dense Network for Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2018.00340openalex-snapshot

Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation

inferredcites →https://doi.org/10.1109/cvpr.2018.00693openalex-snapshot

Frame-Recurrent Video Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2018.00745openalex-snapshot

Squeeze-and-Excitation Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00813openalex-snapshot

Non-local Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2019.00817openalex-snapshot

Image Super-Resolution by Neural Texture Transfer

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00342openalex-snapshot

TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00440openalex-snapshot

Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00573openalex-snapshot

Image Super-Resolution With Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00583openalex-snapshot

Learning Texture Transformer Network for Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00803openalex-snapshot

Video Super-Resolution With Temporal Group Attention

inferredcites →https://doi.org/10.1109/cvpr46437.2021.00491openalex-snapshot

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

inferredcites →https://doi.org/10.1109/cvpr46437.2021.01402openalex-snapshot

GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvprw.2019.00247openalex-snapshot

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

inferredcites →https://doi.org/10.1109/iccphot.2012.6215221openalex-snapshot

Super-resolution from internet-scale scene matching

inferredcites →https://doi.org/10.1109/iccv.2013.241openalex-snapshot

Anchored Neighborhood Regression for Fast Example-Based Super-Resolution

inferredcites →https://doi.org/10.1109/iccv.2017.274openalex-snapshot

Robust Video Super-Resolution with Learned Temporal Dynamics

inferredcites →https://doi.org/10.1109/iccv.2017.479openalex-snapshot

Detail-Revealing Deep Video Super-Resolution

inferredcites →https://doi.org/10.1109/iccv.2017.481openalex-snapshot

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis

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

Image Super-Resolution Using Dense Skip Connections

inferredcites →https://doi.org/10.1109/iccv.2019.00320openalex-snapshot

Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal Correlations

inferredcites →https://doi.org/10.1109/iccv48922.2021.00477openalex-snapshot

Deep Blind Video 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.2010.2050625openalex-snapshot

Image Super-Resolution Via Sparse Representation

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

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.48550/arxiv.1811.00239openalex-snapshot

Progressive Memory Banks for Incremental Domain Adaptation

What points at this work

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

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SCAU-Net: An Efficient Module for Multi-scale Feature Extraction and Aggregation in Video Super-Resolution

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Spatial Attention-Driven Feature Alignment for Underwater Video Super-Resolution

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Kernel adaptive memory network for blind video super-resolution

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A ‘deep’ review of video super-resolution

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STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution

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Long-range zero-shot generative deep network quantization

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TIME: Trajectory and Interaction-based Memory Enhancement network for multi-agent trajectory prediction

inferred← citeshttps://doi.org/10.1038/s41587-025-02553-8openalex-snapshot

A neural network for long-term super-resolution imaging of live cells with reliable confidence quantification

inferred← citeshttps://doi.org/10.1049/ipr2.12699openalex-snapshot

Non‐local neural networks combined with local importance‐based pooling for space‐time video super‐resolution

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Recurrent feature supplementation network for video super-resolution

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Diverse 3D Hand Gesture Prediction from Body Dynamics by Bilateral Hand Disentanglement

inferred← citeshttps://doi.org/10.1109/cvpr52729.2023.02168openalex-snapshot

Structured Sparsity Learning for Efficient Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvpr52733.2024.01804openalex-snapshot

MemFlow: Optical Flow Estimation and Prediction with Memory

inferred← citeshttps://doi.org/10.1109/cvpr52733.2024.02467openalex-snapshot

Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance

inferred← citeshttps://doi.org/10.1109/cvprw59228.2023.00124openalex-snapshot

Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw63382.2024.00628openalex-snapshot

Swift Parameter-free Attention Network for Efficient Super-Resolution

inferred← citeshttps://doi.org/10.1109/icccis56430.2022.10037618openalex-snapshot

Deep Learning Methods for Super Resolution of Video

inferred← citeshttps://doi.org/10.1109/iccv51070.2023.00895openalex-snapshot

Sparse Instance Conditioned Multimodal Trajectory Prediction

inferred← citeshttps://doi.org/10.1109/iccv51070.2023.01137openalex-snapshot

Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-Resolution

inferred← citeshttps://doi.org/10.1109/igarss53475.2024.10642747openalex-snapshot

Hyperspectral Image Denoising Based on Nonlocal Memory-Augmented Spectral Attention

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Real-time Night Surveillance Video Retrieval through Calibrated Denoising and Super-resolution

inferred← citeshttps://doi.org/10.1109/jproc.2025.3613233openalex-snapshot

Deep-Learning-Empowered Super Resolution: A Comprehensive Survey and Future Prospects

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Real-Time Infrared Small Target Detection With Nonlocal Spatial-Temporal Feature Fusion

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Multitemporal Difference and Dynamic Optimization Framework for Multiscale Motion Satellite Video Super-Resolution

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Learning a Local-Global Alignment Network for Satellite Video Super-Resolution

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SAAMU-Net: A Selective Attention Aggregation and Memory-Augmented U-Net Model for Microscopic Medical Image Segmentation

inferred← citeshttps://doi.org/10.1109/tcsvt.2023.3312321openalex-snapshot

Local-Global Temporal Difference Learning for Satellite Video Super-Resolution

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CTVSR: Collaborative Spatial–Temporal Transformer for Video Super-Resolution

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Delving Into Instance Modeling for Weakly Supervised Video Anomaly Detection

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A Survey of Deep Learning Video Super-Resolution

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Hyperspectral Image Super-Resolution Network Based on Cross-Scale Nonlocal Attention

inferred← citeshttps://doi.org/10.1109/tgrs.2023.3291822openalex-snapshot

Deep Blind Super-Resolution for Satellite Video

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Deformable Convolution Alignment and Dynamic Scale-Aware Network for Continuous-Scale Satellite Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/tgrs.2026.3652305openalex-snapshot

EBRNet: Lightweight Enhanced Bidirectional Recurrent Network for Satellite Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/tip.2024.3453048openalex-snapshot

TMP: Temporal Motion Propagation for Online Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/tip.2025.3547298openalex-snapshot

Multi-Axis Feature Diversity Enhancement for Remote Sensing Video Super-Resolution

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Zero-Shot Single-View Point Cloud Reconstruction via Cross-Category Knowledge Transferring

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Reference-based Restoration of Digitized Analog Videotapes

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EdiTor: Edge-guided Transformer for Ghost-free High Dynamic Range Imaging

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SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network

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Fine-Grained Air Pollution Inference at Large-Scale Region Level via 3D Spatiotemporal Attention Super-Resolution Model

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Position-Guided Multi-Head Alignment and Fusion for Video Super-Resolution

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Memory Augmentation and Non-Local Spectral Attention for Hyperspectral Denoising

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Frequency-Aware Enhancement Network for Satellite Video Super-Resolution

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数据驱动的高分辨成像自适应光学技术研究进展（特邀）

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