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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.
Transmission-Guided Bayesian Generative Model for Smoke Segmentation
DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention
Restoring Vision in Hazy Weather with Hierarchical Contrastive Learning
Relationship Quantification of Image Degradations
Encoder-Decoder Network with Guided Transmission Map: Architecture
Dehazed Image Quality Evaluation: From Partial Discrepancy to Blind Perception
Towards Generalization on Real Domain for Single Image Dehazing via Meta-Learning
Semi-UFormer: Semi-supervised Uncertainty-aware Transformer for Image Dehazing
Semantic Structure Enhanced Contrastive Adversarial Hash Network for Cross-media Representation Learning
Deep Fourier Up-Sampling
Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal
Dual-former: Hybrid Self-attention Transformer for Efficient Image Restoration
Rethinking Performance Gains in Image Dehazing Networks
Dual-Scale Single Image Dehazing Via Neural Augmentation
LKD-Net: Large Kernel Convolution Network for Single Image Dehazing
TogetherNet: Bridging Image Restoration and Object Detection Together via Dynamic Enhancement Learning
Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration
Source-Free Domain Adaptation for Real-world Image Dehazing
Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing
Deep Learning Eliminates Massive Dust Storms from Images of Tianwen-1
0/1 Deep Neural Networks via Block Coordinate Descent
Orthogonal Transform based Generative Adversarial Network for Image Dehazing
Compound Multi-branch Feature Fusion for Real Image Restoration
UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning
Towards Efficient Single Image Dehazing and Desnowing
Vision Transformers for Single Image Dehazing
Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction
Near-Infrared Depth-Independent Image Dehazing using Haar Wavelets
Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle
Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning
Single UHD Image Dehazing via Interpretable Pyramid Network
A Novel Encoder-Decoder Network with Guided Transmission Map for Single Image Dehazing
MAXIM: Multi-Axis MLP for Image Processing
Improving Image Restoration by Revisiting Global Information Aggregation
U2-Former: A Nested U-shaped Transformer for Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.