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NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results

https://doi.org/10.1109/cvprw.2019.00250

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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

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/10.1007/978-3-319-16817-3_8openalex-snapshot

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

inferredcites →https://doi.org/10.1109/cvpr.2011.5995614openalex-snapshot

A Bayesian approach to adaptive video 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.2016.206openalex-snapshot

Seven Ways to Improve Example-Based Single Image Super Resolution

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.2017.304openalex-snapshot

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

inferredcites →https://doi.org/10.1109/cvpr.2017.35openalex-snapshot

Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring

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.2018.00179openalex-snapshot

Deep Back-Projection Networks for Super-Resolution

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.2018.00853openalex-snapshot

Scale-Recurrent Network for Deep Image Deblurring

inferredcites →https://doi.org/10.1109/cvpr.2018.00931openalex-snapshot

PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume

inferredcites →https://doi.org/10.1109/cvpr.2018.00936openalex-snapshot

LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation

inferredcites →https://doi.org/10.1109/cvpr.2019.00402openalex-snapshot

Recurrent Back-Projection Network for Video Super-Resolution

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/cvprw.2017.149openalex-snapshot

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

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/cvprw.2018.00130openalex-snapshot

NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results

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

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

inferredcites →https://doi.org/10.1109/cvprw.2019.00249openalex-snapshot

NTIRE 2019 Challenge on Video Deblurring: Methods and Results

inferredcites →https://doi.org/10.1109/cvprw.2019.00251openalex-snapshot

NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study

inferredcites →https://doi.org/10.1109/cvprw.2019.00255openalex-snapshot

Adapting Image Super-Resolution State-Of-The-Arts and Learning Multi-Model Ensemble for Video Super-Resolution

inferredcites →https://doi.org/10.1109/iccv.2015.316openalex-snapshot

FlowNet: Learning Optical Flow with Convolutional Networks

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.2017.37openalex-snapshot

Video Frame Interpolation via Adaptive Separable Convolution

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

Detail-Revealing Deep Video Super-Resolution

inferredcites →https://doi.org/10.1109/iccv.2017.89openalex-snapshot

Deformable Convolutional Networks

inferredcites →https://doi.org/10.1109/icip.1999.817091openalex-snapshot

Dynamic range improvement through multiple exposures

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

Image quality assessment: from error visibility to structural similarity

inferredcites →https://doi.org/10.48550/arxiv.1808.08718openalex-snapshot

Wide Activation for Efficient and Accurate Image Super-Resolution

What points at this work

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

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Video super-resolution based on deep learning: a comprehensive survey

inferred← citeshttps://doi.org/10.1016/j.image.2024.117175openalex-snapshot

A ‘deep’ review of video super-resolution

inferred← citeshttps://doi.org/10.1109/access.2020.3014497openalex-snapshot

Blind Image Quality Assessment for Super Resolution via Optimal Feature Selection

inferred← citeshttps://doi.org/10.1109/access.2022.3144406openalex-snapshot

Flexible Style Image Super-Resolution Using Conditional Objective

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A Survey on Intelligent Solutions for Increased Video Delivery Quality in Cloud–Edge–End Networks

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Space-Time Distillation for Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw.2019.00247openalex-snapshot

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

inferred← citeshttps://doi.org/10.1109/cvprw.2019.00249openalex-snapshot

NTIRE 2019 Challenge on Video Deblurring: Methods and Results

inferred← citeshttps://doi.org/10.1109/cvprw.2019.00255openalex-snapshot

Adapting Image Super-Resolution State-Of-The-Arts and Learning Multi-Model Ensemble for Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw.2019.00258openalex-snapshot

MultiBoot Vsr: Multi-Stage Multi-Reference Bootstrapping for Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw.2019.00269openalex-snapshot

An Empirical Investigation of Efficient Spatio-Temporal Modeling in Video Restoration

inferred← citeshttps://doi.org/10.1109/cvprw50498.2020.00216openalex-snapshot

NTIRE 2020 Challenge on Image and Video Deblurring

inferred← citeshttps://doi.org/10.1109/cvprw53098.2021.00025openalex-snapshot

NTIRE 2021 Challenge on Image Deblurring

inferred← citeshttps://doi.org/10.1109/cvprw53098.2021.00026openalex-snapshot

NTIRE 2021 Challenge on Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw53098.2021.00287openalex-snapshot

Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report

inferred← citeshttps://doi.org/10.1109/cvprw67362.2025.00090openalex-snapshot

Efficient Burst Super-Resolution with One-Step Diffusion

inferred← citeshttps://doi.org/10.1109/cvprw67362.2025.00329openalex-snapshot

Low-Resource Video Super-Resolution using Memory, Wavelets, and Deformable Convolutions

inferred← citeshttps://doi.org/10.1109/icccnt56998.2023.10306622openalex-snapshot

Computer vision approach for motion blur image restoration system

inferred← citeshttps://doi.org/10.1109/iccvw.2019.00421openalex-snapshot

AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results

inferred← citeshttps://doi.org/10.1109/icip49359.2023.10223173openalex-snapshot

Spatio-Temporal Perception-Distortion Trade-Off in Learned Video SR

inferred← citeshttps://doi.org/10.1109/icmew68306.2025.11152100openalex-snapshot

ICME 2025 Grand Challenge on Video Super-Resolution for Video Conferencing

inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10650161openalex-snapshot

Burst Super-Resolution with Diffusion Models for Improving Perceptual Quality

inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10651401openalex-snapshot

Time-series Initialization and Conditioning for Video-agnostic Stabilization of Video Super-Resolution using Recurrent Networks

inferred← citeshttps://doi.org/10.1109/ipas50080.2020.9334961openalex-snapshot

Region-dependent Scale Proposals for Super-Resolution in Object Detection

inferred← citeshttps://doi.org/10.1109/slaai-icai68534.2025.11318427openalex-snapshot

A Flash-Attention-Optimized CNN Transformer Framework for Real-Time Video Restoration

inferred← citeshttps://doi.org/10.1109/tip.2021.3056868openalex-snapshot

Multi-Stage Feature Fusion Network for Video Super-Resolution

inferred← citeshttps://doi.org/10.1109/tip.2021.3101826openalex-snapshot

Compressed Domain Deep Video Super-Resolution

inferred← citeshttps://doi.org/10.11834/jig.220130openalex-snapshot

Deep learning based video-related super-resolution technique： a survey

inferred← citeshttps://doi.org/10.1561/9781680839739openalex-snapshot

Deep Learning for Image/Video Restoration and Super-resolution

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Understanding Deformable Alignment in Video Super-Resolution

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AVM Image Quality Enhancement by Synthetic Image Learning for Supervised Deblurring

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Any-scale Object Detection using Arbitrary-scaled Images

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Neural image enhancement and restoration for time-lapse SPM images

inferred← citeshttps://doi.org/10.48550/arxiv.1905.02716openalex-snapshot

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

inferred← citeshttps://doi.org/10.48550/arxiv.2103.09455openalex-snapshot

Prediction-assistant Frame Super-Resolution for Video Streaming

inferred← citeshttps://doi.org/10.48550/arxiv.2104.00636openalex-snapshot

Distributed Video Adaptive Block Compressive Sensing

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Generative Adversarial Network and ResNet Comparison for Video Super Resolution in Smartphones

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