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Underwater Image Restoration
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Underwater image restoration aims to rectify the distorted colors and present the true colors of the underwater scene.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration
Underwater Image Restoration Through a Prior Guided Hybrid Sense Approach and Extensive Benchmark Analysis
Underwater Image Restoration via Polymorphic Large Kernel CNNs
NeuroPump: Simultaneous Geometric and Color Rectification for Underwater Images
Unified Image Restoration and Enhancement: Degradation Calibrated Cycle Reconstruction Diffusion Model
Blind Underwater Image Restoration using Co-Operational Regressor Networks
Phaseformer: Phase-based Attention Mechanism for Underwater Image Restoration and Beyond
U2NeRF: Unsupervised Underwater Image Restoration and Neural Radiance Fields
Aquatic-GS: A Hybrid 3D Representation for Underwater Scenes
Image Enhancement Based on Histogram-Guided Multiple Transformation Function Estimation
UIE-UnFold: Deep Unfolding Network with Color Priors and Vision Transformer for Underwater Image Enhancement
Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration
Dual High-Order Total Variation Model for Underwater Image Restoration
CE-VAE: Capsule Enhanced Variational AutoEncoder for Underwater Image Enhancement
Osmosis: RGBD Diffusion Prior for Underwater Image Restoration
Atlantis: Enabling Underwater Depth Estimation with Stable Diffusion
Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration
Advanced Underwater Image Restoration in Complex Illumination Conditions
Multiple transformation function estimation for image enhancement
Synergistic Multiscale Detail Refinement via Intrinsic Supervision for Underwater Image Enhancement
Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank
MetaUE: Model-based Meta-learning for Underwater Image Enhancement
U-shape Transformer for Underwater Image Enhancement
HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
Single Underwater Image Restoration by Contrastive Learning
Underwater image filtering: methods, datasets and evaluation
Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations
Enhancement of Underwater Images with Statistical Model of Background Light and Optimization of Transmission Map
Fast Underwater Image Enhancement for Improved Visual Perception
Generalization of the Dark Channel Prior for Single Image Restoration
An Underwater Image Enhancement Benchmark Dataset and Beyond
Enhancing Underwater Imagery using Generative Adversarial Networks
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