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https://doi.org/10.2139/ssrn.4617171

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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-extracted
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
inferredcites →https://doi.org/10.1007/978-3-030-11021-5_5openalex-extracted
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
inferredcites →https://doi.org/10.1007/978-3-030-58595-2_30openalex-extracted
Learning Enriched Features for Real Image Restoration and Enhancement
inferredcites →https://doi.org/10.1007/978-3-030-67070-2_3openalex-extracted
Efficient Image Super-Resolution Using Pixel Attention
inferredcites →https://doi.org/10.1007/978-3-319-46475-6_43openalex-extracted
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
inferredcites →https://doi.org/10.1007/s00371-022-02423-3openalex-extracted
Learning adaptive hyper-guidance via proxy-based bilevel optimization for image enhancement
inferredcites →https://doi.org/10.1016/j.isprsjprs.2018.09.018openalex-extracted
Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network
inferredcites →https://doi.org/10.1016/j.patcog.2016.06.008openalex-extracted
LLNet: A deep autoencoder approach to natural low-light image enhancement
inferredcites →https://doi.org/10.1016/j.patcog.2019.107169openalex-extracted
Blind single image super-resolution with a mixture of deep networks
inferredcites →https://doi.org/10.1016/j.patcog.2020.107475openalex-extracted
Hierarchical dense recursive network for image super-resolution
inferredcites →https://doi.org/10.1016/j.patcog.2020.107798openalex-extracted
Image super-resolution via channel attention and spatial graph convolutional network
inferredcites →https://doi.org/10.1016/j.patcog.2021.108206openalex-extracted
Semi-supervised student-teacher learning for single image super-resolution
inferredcites →https://doi.org/10.1016/j.patcog.2022.109038openalex-extracted
Single image super‐resolution based on progressive fusion of orientation‐aware features
inferredcites →https://doi.org/10.1016/j.patcog.2022.109195openalex-extracted
Brain-like retinex: A biologically plausible retinex algorithm for low light image enhancement
inferredcites →https://doi.org/10.1016/j.patcog.2022.109249openalex-extracted
TreEnhance: A tree search method for low-light image enhancement
inferredcites →https://doi.org/10.1016/j.patcog.2023.109510openalex-extracted
Patch loss: A generic multi-scale perceptual loss for single image super-resolution
inferredcites →https://doi.org/10.1016/j.patcog.2023.109602openalex-extracted
SurroundNet: Towards effective low-light image enhancement
inferredcites →https://doi.org/10.1016/j.patcog.2023.110001openalex-extracted
Low-light image enhancement using gamma correction prior in mixed color spaces
inferredcites →https://doi.org/10.1109/cvpr.2017.19openalex-extracted
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
inferredcites →https://doi.org/10.1109/cvpr.2018.00068openalex-extracted
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
inferredcites →https://doi.org/10.1109/cvpr.2018.00179openalex-extracted
Deep Back-Projection Networks for Super-Resolution
inferredcites →https://doi.org/10.1109/cvpr.2018.00262openalex-extracted
Residual Dense Network for Image Super-Resolution
inferredcites →https://doi.org/10.1109/cvpr.2019.00399openalex-extracted
Feedback Network for Image Super-Resolution
inferredcites →https://doi.org/10.1109/cvpr.2019.00701openalex-extracted
Underexposed Photo Enhancement Using Deep Illumination Estimation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00313openalex-extracted
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00352openalex-extracted
Image Super-Resolution with Non-Local Sparse Attention
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00776openalex-extracted
Data-Free Knowledge Distillation For Image Super-Resolution
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01042openalex-extracted
Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00555openalex-extracted
Toward Fast, Flexible, and Robust Low-Light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00564openalex-extracted
Restormer: Efficient Transformer for High-Resolution Image Restoration
inferredcites →https://doi.org/10.1109/cvpr52729.2023.02142openalex-extracted
Activating More Pixels in Image Super-Resolution Transformer
inferredcites →https://doi.org/10.1109/cvprw56347.2022.00092openalex-extracted
Residual Local Feature Network for Efficient Super-Resolution
inferredcites →https://doi.org/10.1109/taes.1983.309421openalex-extracted
Hardware-Constrained Hybrid Coding of Video Imagery
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-extracted
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/tip.2006.888338openalex-extracted
Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy
inferredcites →https://doi.org/10.1109/tip.2011.2109730openalex-extracted
FSIM: A Feature Similarity Index for Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2013.2261309openalex-extracted
Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images
inferredcites →https://doi.org/10.1109/tip.2020.2981922openalex-extracted
Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study
inferredcites →https://doi.org/10.1109/tip.2021.3051462openalex-extracted
EnlightenGAN: Deep Light Enhancement Without Paired Supervision
inferredcites →https://doi.org/10.1109/tpami.2020.2982166openalex-extracted
Deep Learning for Image Super-Resolution: A Survey
inferredcites →https://doi.org/10.1109/tpami.2021.3063604openalex-extracted
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
inferredcites →https://doi.org/10.1109/tpami.2021.3126387openalex-extracted
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
inferredcites →https://doi.org/10.1109/tpami.2021.3132674openalex-extracted
Investigating Bi-Level Optimization for Learning and Vision From a Unified Perspective: A Survey and Beyond
inferredcites →https://doi.org/10.1145/3343031.3350926openalex-extracted
Kindling the Darkness
inferredcites →https://doi.org/10.1145/3495258openalex-extracted
Deep Illumination-Enhanced Face Super-Resolution Network for Low-Light Images
inferredcites →https://doi.org/10.1364/josa.61.000001openalex-extracted
Lightness and Retinex Theory
inferredcites →https://doi.org/10.1609/aaai.v37i3.25364openalex-extracted
Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
inferredcites →https://doi.org/10.2139/ssrn.4362440openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.1905.04161openalex-extracted
Kindling the Darkness: A Practical Low-light Image Enhancer
inferredcites →https://doi.org/10.48550/arxiv.2003.06792openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2010.01073openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2012.05609openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2110.05098openalex-extracted
SurroundNet: Towards Effective Low-Light Image Enhancement
inferredcites →https://doi.org/10.48550/arxiv.2111.09881openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2204.10137openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2205.04437openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2205.12639openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2212.11548openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2303.09735openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2307.15257openalex-extracted
inferredcites →https://doi.org/10.5281/zenodo.5234968openalex-extracted
RELLISUR: A Real Low-Light Image Super-Resolution Dataset
inferredcites →https://doi.org/10.5281/zenodo.5234969openalex-extracted

What points at this work

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

inferred← citeshttps://doi.org/10.1109/tmm.2024.3355634openalex-snapshot
Perceptual Decoupling With Heterogeneous Auxiliary Tasks for Joint Low-Light Image Enhancement and Deblurring
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