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Path-Restore: Learning Network Path Selection for Image Restoration

https://doi.org/10.1109/tpami.2021.3096255

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What this work says

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

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Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

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ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

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Building Dual-Domain Representations for Compression Artifacts Reduction

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Perceptual Losses for Real-Time Style Transfer and Super-Resolution

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Simple statistical gradient-following algorithms for connectionist reinforcement learning

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Fields of Experts

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Convolutional Networks with Adaptive Inference Graphs

inferredcites →https://doi.org/10.1016/j.jvcir.2018.01.012openalex-snapshot

RENOIR – A dataset for real low-light image noise reduction

inferredcites →https://doi.org/10.1023/a:1022672621406openalex-snapshot

Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

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Human-level control through deep reinforcement learning

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Mastering the game of Go without human knowledge

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Deep Residual Learning for Image Recognition

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Toward Convolutional Blind Denoising of Real Photographs

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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

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Unprocessing Images for Learned Raw Denoising

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

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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/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/iccv.2015.73openalex-snapshot

Compression Artifacts Reduction by a Deep Convolutional Network

inferredcites →https://doi.org/10.1109/iccv.2019.00325openalex-snapshot

Real Image Denoising With Feature Attention

inferredcites →https://doi.org/10.1109/icip.2007.4378954openalex-snapshot

Color Image Denoising via Sparse 3D Collaborative Filtering with Grouping Constraint in Luminance-Chrominance Space

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Waterloo Exploration Database: New Challenges for Image Quality Assessment Models

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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

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FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising

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Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

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inferredcites →https://doi.org/10.48550/arxiv.1611.02167openalex-snapshot

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inferredcites →https://doi.org/10.48550/arxiv.1709.09602openalex-snapshot

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TensorFlow: A system for large-scale machine learning

What points at this work

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Irregular Facades: A Dataset for Semantic Segmentation of the Free Facade of Modern Buildings

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Blind Restoration of Atmospheric Turbulence-Degraded Images Based on Curriculum Learning

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A Side-Lobe Denoise Process for ISAR Imaging Applications: Combined Fast Clean and Spatial Focus Technique

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Feature Intensification Using Perception-Guided Regional Classification for Remote Sensing Image Super-Resolution

inferred← citeshttps://doi.org/10.3390/s19173809openalex-snapshot

Dynamic Residual Dense Network for Image Denoising

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Innovative Dual-Stage Blind Noise Reduction in Real-World Images Using Multi-Scale Convolutions and Dual Attention Mechanisms

inferred← citeshttps://doi.org/10.46647/ijetms.2024.v08i03.009openalex-snapshot

IMAGE RECONSTRUCTION OF OLD DAMAGED PHOTOS

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.2001.10853openalex-snapshot

H-OWAN: Multi-distorted Image Restoration with Tensor 1x1 Convolution

inferred← citeshttps://doi.org/10.48550/arxiv.2002.09611openalex-snapshot

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

inferred← citeshttps://doi.org/10.48550/arxiv.2010.12422openalex-snapshot

Progressive Training of Multi-level Wavelet Residual Networks for Image Denoising

inferred← citeshttps://doi.org/10.48550/arxiv.2012.05703openalex-snapshot

TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems

inferred← citeshttps://doi.org/10.48550/arxiv.2107.05318openalex-snapshot

R3L: Connecting Deep Reinforcement Learning to Recurrent Neural Networks for Image Denoising via Residual Recovery

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