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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.
Haze Removal via Regional Saturation-Value Translation and Soft Segmentation
DHFormer: A Vision Transformer-Based Attention Module for Image Dehazing
Encoder-minimal and Decoder-minimal Framework for Remote Sensing Image Dehazing
Image Restoration via Frequency Selection
Controlling Vision-Language Models for Multi-Task Image Restoration
Prompt-based test-time real image dehazing: a novel pipeline
Accurate and lightweight dehazing via multi-receptive-field non-local network and novel contrastive regularization
Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
MB-TaylorFormer: Multi-branch Efficient Transformer Expanded by Taylor Formula for Image Dehazing
High-quality Image Dehazing with Diffusion Model
Frequency Compensated Diffusion Model for Real-scene Dehazing
Mutual Information-driven Triple Interaction Network for Efficient Image Dehazing
Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution
Visibility Enhancement for Low-light Hazy Scenarios
Decomposition Ascribed Synergistic Learning for Unified Image Restoration
DFR-Net: Density Feature Refinement Network for Image Dehazing Utilizing Haze Density Difference
Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images
RB-Dust -- A Reference-based Dataset for Vision-based Dust Removal
Illumination Controllable Dehazing Network based on Unsupervised Retinex Embedding
SAGE-NDVI: A Stereotype-Breaking Evaluation Metric for Remote Sensing Image Dehazing Using Satellite-to-Ground NDVI Knowledge
MixDehazeNet : Mix Structure Block For Image Dehazing Network
SimHaze: game engine simulated data for real-world dehazing
NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer
Streamlined Global and Local Features Combinator (SGLC) for High Resolution Image Dehazing
Dehazing-NeRF: Neural Radiance Fields from Hazy Images
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing
A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformer
RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors
Fooling the Image Dehazing Models by First Order Gradient
4K-HAZE: A Dehazing Benchmark with 4K Resolution Hazy and Haze-Free Images
Curricular Contrastive Regularization for Physics-aware Single Image Dehazing
Neural Preset for Color Style Transfer
Reliable Image Dehazing by NeRF
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.