Papers with Code 아카이브
Image Dehazing
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<span style="color:grey; opacity: 0.6">( Image credit: Densely Connected Pyramid Dehazing Network )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Perceiving and Modeling Density is All You Need for Image Dehazing
3D modelling of survey scene from images enhanced with a multi-exposure fusion
Multi-Scale Single Image Dehazing Using Laplacian and Gaussian Pyramids
Single image dehazing via combining the prior knowledge and CNNs
A review of Generative Adversarial Networks (GANs) and its applications in a wide variety of disciplines -- From Medical to Remote Sensing
DAMix: A Density-Aware Mixup Augmentation for Single Image Dehazing under Domain Shift
Single Image Dehazing with An Independent Detail-Recovery Network
Complementary Feature Enhanced Network with Vision Transformer for Image Dehazing
Efficient Re-parameterization Residual Attention Network For Nonhomogeneous Image Dehazing
Fully Non-Homogeneous Atmospheric Scattering Modeling with Convolutional Neural Networks for Single Image Dehazing
From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data
A Single Image Dehazing Technique Using the Dual Transmission Maps Strategy and Gradient-Domain Guided Image Filtering
Unsupervised Neural Rendering for Image Hazing
A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning
Uformer: A General U-Shaped Transformer for Image Restoration
T-Net: Deep Stacked Scale-Iteration Network for Image Dehazing
Pyramid Fusion Dark Channel Prior for Single Image Dehazing
Contrastive Learning for Compact Single Image Dehazing
A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learning
Non-Homogeneous Haze Removal via Artificial Scene Prior and Bidimensional Graph Reasoning
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing
Progressive residual learning for single image dehazing
Evaluating COPY-BLEND Augmentation for Low Level Vision Tasks
Efficient and Accurate Multi-scale Topological Network for Single Image Dehazing
Progressive Depth Learning for Single Image Dehazing
A GAN-Based Input-Size Flexibility Model for Single Image Dehazing
Two-Step Image Dehazing with Intra-domain and Inter-domain Adaptation
Indirect Domain Shift for Single Image Dehazing
FWB-Net:Front White Balance Network for Color Shift Correction in Single Image Dehazing via Atmospheric Light Estimation
Towards Domain Invariant Single Image Dehazing
Modeling Deep Learning Based Privacy Attacks on Physical Mail
Domain-Aware Unsupervised Hyperspectral Reconstruction for Aerial Image Dehazing
Blind Video Temporal Consistency via Deep Video Prior
Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed Images
Evaluating Single Image Dehazing Methods Under Realistic Sunlight Haze
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.