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Learning Trajectory-Aware Transformer for Video Super-Resolution

https://doi.org/10.1109/cvpr52688.2022.00560

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01219-9_7openalex-snapshot

Spatio-Temporal Transformer Network for Video Restoration

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/10.1007/978-3-030-58452-8_13openalex-snapshot

End-to-End Object Detection with Transformers

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/10.1007/978-3-030-58607-2_20openalex-snapshot

MuCAN: Multi-correspondence Aggregation Network for Video Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-030-58610-2_38openalex-snapshot

Video Super-Resolution with Recurrent Structure-Detail Network

inferredcites →https://doi.org/10.1007/s11263-012-0594-8openalex-snapshot

Dense Trajectories and Motion Boundary Descriptors for Action Recognition

inferredcites →https://doi.org/10.1007/s11263-018-01144-2openalex-snapshot

Video Enhancement with Task-Oriented Flow

inferredcites →https://doi.org/10.1016/j.sigpro.2009.09.002openalex-snapshot

A super-resolution reconstruction algorithm for surveillance images

inferredcites →https://doi.org/10.1109/cvpr.2017.291openalex-snapshot

Optical Flow Estimation Using a Spatial Pyramid 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.2018.00340openalex-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.2019.00402openalex-snapshot

Recurrent Back-Projection Network for Video Super-Resolution

inferredcites →https://doi.org/10.1109/cvpr.2019.01077openalex-snapshot

Fast Spatio-Temporal Residual 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/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/cvpr46437.2021.00632openalex-snapshot

Temporal Modulation Network for Controllable Space-Time Video 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/cvprw.2019.00251openalex-snapshot

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

inferredcites →https://doi.org/10.1109/iccv.2013.441openalex-snapshot

Action Recognition with Improved Trajectories

inferredcites →https://doi.org/10.1109/iccv.2015.510openalex-snapshot

Learning Spatiotemporal Features with 3D Convolutional Networks

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/iccv.2019.00320openalex-snapshot

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

inferredcites →https://doi.org/10.1109/iccv48922.2021.00439openalex-snapshot

Omniscient Video Super-Resolution

inferredcites →https://doi.org/10.1109/iccvw.2019.00431openalex-snapshot

Efficient Video Super-Resolution through Recurrent Latent Space Propagation

inferredcites →https://doi.org/10.1109/icip.2019.8803297openalex-snapshot

Video Super-Resolution Based on 3D-CNNS with Consideration of Scene Change

inferredcites →https://doi.org/10.1109/icpr.2014.762openalex-snapshot

Super-resolution System for 4K-HDTV

inferredcites →https://doi.org/10.1109/lgrs.2017.2766204openalex-snapshot

Video Satellite Imagery Super Resolution via Convolutional Neural Networks

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/tpami.2013.127openalex-snapshot

On Bayesian Adaptive Video Super Resolution

inferredcites →https://doi.org/10.1109/tpami.2017.2701380openalex-snapshot

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks

inferredcites →https://doi.org/10.1142/s0218488598000094openalex-snapshot

The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions

inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot

AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale

inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot

Exploiting Generative AI to Scale up Intelligent Tutoring Systems

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

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.48550/arxiv.1812.09079openalex-snapshot

3DSRnet: Video Super-resolution using 3D Convolutional Neural Networks

inferredcites →https://doi.org/10.48550/arxiv.2002.06460openalex-snapshot

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery

inferredcites →https://doi.org/10.48550/arxiv.2008.05765openalex-snapshot

Revisiting Temporal Modeling for Video Super-resolution

inferredcites →https://doi.org/10.48550/arxiv.2106.06847openalex-snapshot

Video Super-Resolution Transformer

What points at this work

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

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Research on Video Super-Resolution Technology Based on Multi-scale Spatiotemporal Information Aggregation

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QueryCDR: Query-Based Controllable Distortion Rectification Network for Fisheye Images

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Event-Adapted Video Super-Resolution

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AdaDiffSR: Adaptive Region-Aware Dynamic Acceleration Diffusion Model for Real-World Image Super-Resolution

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Kalman-Inspired Feature Propagation for Video Face Super-Resolution

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IFRFNet: Iterative Frequency Restoration-Fusion Network for Fast System Matrix Calibration on Magnetic Particle Image

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AVSR-Diff: Scale-Agnostic Diffusion Priors for Temporally Consistent Arbitrary-Scale Video Super-Resolution

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

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Auxiliary Features-Guided Cross-Frame Transformer for Rendered Sequences Super-Resolution

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More and Larger Auxiliary Feature-Guided Spatial-Temporal Super-Resolution for Rendered Sequences

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Lightweight Spatio-Temporal Attention Network for Video Super-Resolution

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Real-EVE: Real-Time Edge-Assist Video Enhancement for Joint Denoising and Super-Resolution

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3RE-Net: Joint Loss-REcovery and Super-REsolution Neural Network for REal-Time Video

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Self-guided Transformer for Video Super-Resolution

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IFIC3A-VSR: A Computational Accelerated Video Super-Resolution Network Based on Inter-frame Information Complexity Classification

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Advances in artificial intelligence: a review for the creative industries

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Bidirectional Multi-scale Deformable Attention for Video Super-Resolution

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Identification of Geochemical Anomalies Using an End-to-End Transformer

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Reference-based image super-resolution with attention extraction and pooling of residuals

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SAVSR++: An All-Stage Scale-Aware and Temporal Omniscient Framework for Arbitrary-Scale Video Super-Resolution

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Space-time video super-resolution via multi-scale feature interpolation and temporal feature fusion

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Attention-guided video super-resolution with recurrent multi-scale spatial–temporal transformer

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A Survey of Generative Techniques for Spatial-Temporal Data Mining

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TAFCNet: Task-aware feature coupling network for joint image motion deblurring and super-resolution

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Enhancing video smoothness and clarity: A unified survey of frame interpolation, super-resolution, and space–time super-resolution

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Perception-coherent video super-resolution via Top-K Mamba: Unified global–local spatio-temporal feature learning

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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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PhaseVSRnet: Deep complex network for phase-based satellite video super-resolution

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Cross-scale hierarchical spatio-temporal transformer for video enhancement

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Enhancing space–time video super-resolution via spatial–temporal feature interaction

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Looking beyond input frames: Self-supervised adaptation for video super-resolution

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Image super resolution of Thangka murals using multi-scale feature assisted transformer and hybrid attention

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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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Recurrent Feature Updating Network for Video Super-Resolution

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Trajectory-Aware Deformable Transformer for Contextual Video Prediction

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Video Super-Resolution with Recurrent High and Low-Frequency Information Propagation

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Multi-frame Correlated Representation Network for Video Super-Resolution

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FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring

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Neural Super-Resolution for Real-Time Rendering with Radiance Demodulation

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Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution

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Learning Large-Factor EM Image Super-Resolution with Generative Priors

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Motion-Adaptive Separable Collaborative Filters for Blind Motion Deblurring

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Zero-Reference Low-Light Enhancement via Physical Quadruple Priors

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VideoGigaGAN: Towards Detail-rich Video Super-Resolution

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Event-based Video Super-Resolution via State Space Models

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

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VIhanceD: Efficient Video Super Resolution for Edge Devices

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DATA-VSR: Dynamic Trajectory Attention and Texture Adaptive Rooter for Video Super-Resolution

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FSI: Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras

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SRFormer: Permuted Self-Attention for Single Image Super-Resolution

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Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution

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Learning Data-Driven Vector-Quantized Degradation Model for Animation Video Super-Resolution

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Bridging Diffusion Models and 3D Representations: A 3D Consistent Super-Resolution Framework

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

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Joint Video Denoising and Super-Resolution Network for IoT Cameras

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

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VMG: Rethinking U-Net Architecture for Video Super-Resolution

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PulseFormer: Continuous Remote Heart Rate Measurement Through Zoomed Time-Spectral Attention

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Temporal Consistency Learning of Inter-Frames for Video Super-Resolution

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InstanceSR: Efficient Reconstructing Small Object With Differential Instance-Level Super-Resolution

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CDC-VSR: Unifying Cross-Domain Continuity for High-Quality Video Super-Resolution

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Hyper-Laplacian Prior for Remote Sensing Image Super-Resolution

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Compression-Oriented Video Super-Resolution

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Global Spatial-Temporal Information-Based Residual ConvLSTM for Video Space-Time Super-Resolution

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Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-Local Spatial-Temporal Similarity

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Collaborative Feedback Discriminative Propagation for Video Super-Resolution

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SRFormerV2: Taking a Closer Look at Permuted Self-Attention for Image Super-Resolution

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DaBiT: Depth and Blur Informed Transformer for Video Focal Deblurring

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TempDiff: Enhancing Temporal‐awareness in Latent Diffusion for Real‐World Video Super‐Resolution

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Video super-resolution via nonlocal deformable alignment and frame recursive progressive fusion network

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Sequential Affinity Learning for Video Restoration

inferred← citeshttps://doi.org/10.1145/3581783.3612001openalex-snapshot

Mask-Guided Progressive Network for Joint Raindrop and Rain Streak Removal in Videos

inferred← citeshttps://doi.org/10.1145/3581783.3612595openalex-snapshot

Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning

inferred← citeshttps://doi.org/10.1145/3652583.3658031openalex-snapshot

DeepEnhancer: Temporally Consistent Focal Transformer for Comprehensive Video Enhancement

inferred← citeshttps://doi.org/10.1609/aaai.v37i1.25158openalex-snapshot

TransVCL: Attention-Enhanced Video Copy Localization Network with Flexible Supervision

inferred← citeshttps://doi.org/10.1609/aaai.v38i4.28144openalex-snapshot

Decoupling Degradations with Recurrent Network for Video Restoration in Under-Display Camera

inferred← citeshttps://doi.org/10.1609/aaai.v38i7.28581openalex-snapshot

Optical Flow for Spike Camera with Hierarchical Spatial-Temporal Spike Fusion

inferred← citeshttps://doi.org/10.24963/ijcai.2023/76openalex-snapshot

DFVSR: Directional Frequency Video Super-Resolution via Asymmetric and Enhancement Alignment Network

inferred← citeshttps://doi.org/10.3390/app152111828openalex-snapshot

Super-Resolution Task Inference Acceleration for In-Vehicle Real-Time Video via Edge–End Collaboration

inferred← citeshttps://doi.org/10.3390/electronics11203370openalex-snapshot

ASK-ViT: A Model with Improved ViT Robustness through Incorporating SK Modules Using Adversarial Training

inferred← citeshttps://doi.org/10.3390/electronics12214452openalex-snapshot

FSTT: Flow-Guided Spatial Temporal Transformer for Deep Video Inpainting

inferred← citeshttps://doi.org/10.3390/electronics13224372openalex-snapshot

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

inferred← citeshttps://doi.org/10.3390/info16121020openalex-snapshot

Digital Surface Model and Fractal-Guided Multi-Directional Network for Remote Sensing Image Super-Resolution

inferred← citeshttps://doi.org/10.3390/s23208574openalex-snapshot

A Lightweight Recurrent Grouping Attention Network for Video Super-Resolution

inferred← citeshttps://doi.org/10.36227/techrxiv.171172801.19993069/v1openalex-snapshot

A Survey on Generative AI and LLM for Video Generation, Understanding, and Streaming

inferred← citeshttps://doi.org/10.36227/techrxiv.23896986openalex-snapshot

A Methodical Study of Deep Learning Based Video Super-Resolution

inferred← citeshttps://doi.org/10.36227/techrxiv.23896986.v1openalex-snapshot

A Methodical Study of Deep Learning Based Video Super-Resolution

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