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Towards Real-Time Advancement of Underwater Visual Quality With GAN

https://doi.org/10.1109/tie.2019.2893840
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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-319-46454-1_36openalex-snapshot
Generative Visual Manipulation on the Natural Image Manifold
inferredcites →https://doi.org/10.1007/978-3-319-46475-6_43openalex-snapshot
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
inferredcites →https://doi.org/10.1007/978-3-658-40442-0_9openalex-snapshot
Generative Adversarial Nets
inferredcites →https://doi.org/10.1016/b978-0-12-336156-1.50061-6openalex-snapshot
Contrast Limited Adaptive Histogram Equalization
inferredcites →https://doi.org/10.1016/j.jvcir.2014.11.006openalex-snapshot
Automatic Red-Channel underwater image restoration
inferredcites →https://doi.org/10.1023/b:visi.0000029664.99615.94openalex-snapshot
Distinctive Image Features from Scale-Invariant Keypoints
inferredcites →https://doi.org/10.1109/cvpr.2004.1315078openalex-snapshot
Clear underwater vision
inferredcites →https://doi.org/10.1109/cvpr.2012.6247661openalex-snapshot
Enhancing underwater images and videos by fusion
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.2017.632openalex-snapshot
Image-to-Image Translation with Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/cyber.2017.8446363openalex-snapshot
A Real-time and Unsupervised Advancement Scheme for Underwater Machine Vision
inferredcites →https://doi.org/10.1109/iccv.2017.244openalex-snapshot
Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
inferredcites →https://doi.org/10.1109/iccv.2017.304openalex-snapshot
Least Squares Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/joe.2015.2469915openalex-snapshot
Human-Visual-System-Inspired Underwater Image Quality Measures
inferredcites →https://doi.org/10.1109/oceans.2016.7761342openalex-snapshot
Estimation of ambient light and transmission map with common convolutional architecture
inferredcites →https://doi.org/10.1109/tcsvt.2014.2357093openalex-snapshot
Tracking Live Fish From Low-Contrast and Low-Frame-Rate Stereo Videos
inferredcites →https://doi.org/10.1109/tcyb.2019.2894261openalex-snapshot
Temporally Identity-Aware SSD With Attentional LSTM
inferredcites →https://doi.org/10.1109/tip.2011.2179666openalex-snapshot
Underwater Image Enhancement by Wavelength Compensation and Dehazing
inferredcites →https://doi.org/10.1109/tip.2015.2474701openalex-snapshot
A Probabilistic Method for Image Enhancement With Simultaneous Illumination and Reflectance Estimation
inferredcites →https://doi.org/10.1109/tip.2015.2491020openalex-snapshot
An Underwater Color Image Quality Evaluation Metric
inferredcites →https://doi.org/10.1109/tip.2016.2612882openalex-snapshot
Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior
inferredcites →https://doi.org/10.1109/tip.2017.2663846openalex-snapshot
Underwater Image Restoration Based on Image Blurriness and Light Absorption
inferredcites →https://doi.org/10.1109/tpami.1986.4767851openalex-snapshot
A Computational Approach to Edge Detection
inferredcites →https://doi.org/10.1109/tpami.2007.70827openalex-snapshot
A Spatially Variant White-Patch and Gray-World Method for Color Image Enhancement Driven by Local Contrast
inferredcites →https://doi.org/10.1109/tpami.2010.168openalex-snapshot
Single Image Haze Removal Using Dark Channel Prior
inferredcites →https://doi.org/10.1364/josa.54.000052openalex-snapshot
Modulation Transfer Function Associated with Image Transmission through Turbulent Media
inferredcites →https://doi.org/10.3156/jsoft.29.5_177_2openalex-snapshot
GAN（Generative Adversarial Nets）
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.48550/arxiv.1411.1784openalex-snapshot
Conditional Generative Adversarial Nets
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1511.06434openalex-snapshot
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1701.02676openalex-snapshot
Unsupervised Image-to-Image Translation with Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1805.08318openalex-snapshot
Self-Attention Generative Adversarial Networks
inferredcites →https://doi.org/10.5244/c.2.23openalex-snapshot
A Combined Corner and Edge Detector
inferredcites →https://doi.org/10.5244/c.29.125openalex-snapshot
Hierarchical rank-based veiling light estimation for underwater dehazing

What points at this work

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

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Underwater Image Enhancement by Combining Multi-Attention with Recurrent Residual Convolutional U-Net (Acu-Net)
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Beneath the Surface: The Role of Underwater Image Enhancement in Object Detection
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Pre- and Post-processing on Generative Adversarial Networks for Old Photos Restoration: A Case Study
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Underwater Single Image Restoration Using Modified Cycle GAN
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Improved Deep Learning Approach for Underwater Image Enhancement
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Color Correction of Cervical Exfoliated Cell Micrographs Using an Improved CycleGAN Model
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A two-stage and two-branch generative adversarial network-based underwater image enhancement
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Depth-guided color correction and multi-scale Retinex network for underwater image enhancement
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Unsupervised anomaly detection in the textile texture database
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Underwater image enhancement method via multi-feature prior fusion
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Multiple attentional path aggregation network for marine object detection
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Underwater vision enhancement technologies: a comprehensive review, challenges, and recent trends
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Underwater vision enhancement based on GAN with dehazing evaluation
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Potential of generative adversarial net algorithms in image and video processing applications– a survey
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Underwater optical image processing based on double threshold judgements and optimized red dark channel prior method
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Underwater image restoration based on exponentiated mean local variance and extrinsic prior
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M-PFGMNet: multi-pose feature generation mapping network for visual object tracking
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Learning multiscale pipeline gated fusion for underwater image enhancement
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Zero-reference single underwater image enhancement
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Underwater single-image restoration based on modified generative adversarial net
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Underwater image enhancement by combining multi-attention with recurrent residual convolutional U-Net
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U-TWGAN: Underwater image enhancement via wavelet-transformer and sparse multilayer perceptrons generative adversarial network
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Content-guided attention-based feature fusion network for underwater image enhancement
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TEGAN: Transformer Embedded Generative Adversarial Network for Underwater Image Enhancement
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On-board classification of underwater images using hybrid classical-quantum CNN-based method
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VEGAN: CCTV video quality enhancement with GAN-based foreground separation and super-resolution
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Enhancement of underwater dam crack images using multi-feature fusion
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Unsupervised dam crack image segmentation algorithm based on adversarial learning and image fusion
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SFP-Net: Scatter-feature-perception network for underwater image enhancement
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Enhancing underwater image via adaptive color and contrast enhancement, and denoising
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Enhancing underwater image via color correction and Bi-interval contrast enhancement
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Underwater image restoration by color compensation and color-line model
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Underwater image enhancement via integrated RGB and LAB color models
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Conditional generative adversarial network with dual-branch progressive generator for underwater image enhancement
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Underwater bubble plume image generative model based on noise prior and multi conditional labels
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A Dataset for Detection and Segmentation of Underwater Marine Debris in Shallow Waters
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DGC‐UWnet: Underwater image enhancement based on computation‐efficient convolution and channel shuffle
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FCUnet: An Underwater Image Enhancement Hybrid Network via Fused Feature‐Guided Cross‐Attention
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Highly Stretchable CIP–PDMS Composites with Partial Interface Bonding for Electromagnetic Noise Suppression in GHz Frequency Range
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Semi-supervised advancement of underwater visual quality
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A Review on Underwater Image Enhancement Techniques
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Two-subnet fusion for perceptual quality driven based underwater image enhancement
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PointNet-Based Jitter Decomposition on Point Cloud of Jitter Histogram
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A Method of Image Enhancement in Shallow Water with Underwater System
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WSUIE: Weakly Supervised Underwater Image Enhancement for Improved Visual Perception
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Adaptive Learning Attention Network for Underwater Image Enhancement
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Domain-Adaptive Benthonic Organism Detection via Uniformizing Light Field and Color Distribution
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Jitter Decomposition by Convolutional Neural Networks
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Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks
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Data Augmentation Considering Distribution Discrepancy for Fault Diagnosis of Drilling Process With Limited Samples
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Fault Detection and Identification of Underwater Thruster Without Fault Sample Based on Adversarial Variational Autoencoder
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A Spatial and Geometry Feature-Based Quality Assessment Model for the Light Field Images
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Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement
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Domain Adaptation for Underwater Image Enhancement
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Visual Telepresence for Underwater Manipulation
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Swin transformer and fusion for underwater image enhancement
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A review of underwater object detection methods based on deep learning
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Multiautonomous underwater vehicle consistent collaborative hunting method based on generative adversarial network
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Underwater image restoration via adaptive color balance and multi-purpose oriented contrast enhancement
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An optimized GAN method based on the Que-Attn and contrastive learning for underwater image enhancement
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A novel robotic visual perception framework for underwater operation
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Underwater Image Enhancement by Combining Multi-Attention with Recurrent Residual Convolutional U-Net (Acu-Net)
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Underwater Color Correction via Deep Reinforcement Learning
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Comparison of GAN Deep Learning Methods for Underwater Optical Image Enhancement
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Underwater Diver Image Enhancement via Dual-Guided Filtering
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Fast underwater image enhancement based on a generative adversarial framework
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An underwater imaging method of enhancement via multi-scale weighted fusion
inferred← citeshttps://doi.org/10.3390/app13169419openalex-snapshot
LPS-Net: Lightweight Parallel Strategy Network for Underwater Image Enhancement
inferred← citeshttps://doi.org/10.3390/electronics14122411openalex-snapshot
DeepSeaNet: An Efficient UIE Deep Network
inferred← citeshttps://doi.org/10.3390/jimaging12010018openalex-snapshot
Revisiting Underwater Image Enhancement for Object Detection: A Unified Quality–Detection Evaluation Framework
inferred← citeshttps://doi.org/10.3390/jmse13050899openalex-snapshot
Comparative Analysis of Traditional and Deep Learning Approaches for Underwater Remote Sensing Image Enhancement: A Quantitative Study
inferred← citeshttps://doi.org/10.3390/jmse7070200openalex-snapshot
Adaptive Weighted Multi-Discriminator CycleGAN for Underwater Image Enhancement
inferred← citeshttps://doi.org/10.3390/rs16203773openalex-snapshot
Underwater Optical Imaging: Methods, Applications and Perspectives
inferred← citeshttps://doi.org/10.3390/s22155632openalex-snapshot
Recognition Method of Massage Techniques Based on Attention Mechanism and Convolutional Long Short-Term Memory Neural Network
inferred← citeshttps://doi.org/10.3390/s23041990openalex-snapshot
Research Challenges, Recent Advances, and Popular Datasets in Deep Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.3390/s23198297openalex-snapshot
DRGAN: Dense Residual Generative Adversarial Network for Image Enhancement in an Underwater Autonomous Driving Device
inferred← citeshttps://doi.org/10.3390/s24144757openalex-snapshot
Improving Rebar Twist Prediction Exploiting Unified-Channel Attention-Based Image Restoration and Regression Techniques
inferred← citeshttps://doi.org/10.36227/techrxiv.19350389openalex-snapshot
Research Challenges, Recent Advances and Benchmark Datasets in Deep-Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.36227/techrxiv.19350389.v1openalex-snapshot
Research Challenges, Recent Advances and Benchmark Datasets in Deep-Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.36227/techrxiv.19350389.v2openalex-snapshot
Research Challenges, Recent Advances and Benchmark Datasets in Deep-Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.36227/techrxiv.19350389.v3openalex-snapshot
Research Challenges, Recent Advances and Benchmark Datasets in Deep-Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.36227/techrxiv.19350389.v4openalex-snapshot
Research Challenges, Recent Advances and Benchmark Datasets in Deep-Learning-Based Underwater Marine Object Detection: A Review
inferred← citeshttps://doi.org/10.3837/tiis.2022.08.005openalex-snapshot
Recovery of underwater images based on the attention mechanism and SOS mechanism
inferred← citeshttps://doi.org/10.48175/ijarsct-8838openalex-snapshot
Underwater Image Enhancement using Different Techniques
inferred← citeshttps://doi.org/10.48550/arxiv.1901.05320openalex-snapshot
Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions
inferred← citeshttps://doi.org/10.48550/arxiv.1906.06819openalex-snapshot
A Fusion Adversarial Underwater Image Enhancement Network with a Public Test Dataset
inferred← citeshttps://doi.org/10.48550/arxiv.2003.01913openalex-snapshot
Reveal of Domain Effect: How Visual Restoration Contributes to Object Detection in Aquatic Scenes
inferred← citeshttps://doi.org/10.70675/044e7500zfd93z4c6az8457z4809ad535daeopenalex-snapshot
Learning salient information with neural networks for cosmological analysis
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