Papers Single Image Dehazing
“Single Image Dehazing” 태그가 달린 논문 136편 · 필터 해제
Efficient Real-World Dehazing via Physics-Inspired Global-Local Decoupling
Real-world single image dehazing is highly ill-posed due to spatially and spectrally varying scattering, while practical deployment demands lightweight and low-latency models. Existing approaches either rely on fragile p…
Single Image DehazingObject DetectionDehaze-GaussianImage: Zero-Shot Dehazing via Efficient 2D Gaussian Splatting Representation
Existing single image dehazing methods are often constrained by computational redundancy in pixel-level optimization and the lack of physical interpretability in implicit neural networks. These limitations hinder the bal…
Single Image DehazingZero-Shot LearningFi-Gaussian: Frequency-Aware Implicit Gaussian Splatting for Single Image Dehazing
Single image dehazing continues to be hindered by the loss of high-frequency details and the difficulty of accurate physical scattering modeling. To address these issues, we propose Fi-Gaussian, a frequency-aware implici…
Single Image DehazingPoint CloudsMulti-Branch Non-Homogeneous Image Dehazing via Concentration Partitioning and Image Fusion
Existing single image dehazing methods have demonstrated satisfactory performance on homogeneous thin-haze images; however, they often struggle with non-homogeneous hazy images that exhibit spatially varying haze concent…
Single Image DehazingImage EnhancementZID-Net: Zero-Inference Diffusion Prior Decoupling Network for Single Image Dehazing
Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks struggle to learn robust priors for dense and non-homogeneous haze. Conver…
Computational EfficiencySingle Image DehazingU-Net-Like Spiking Neural Networks for Single Image Dehazing
Image dehazing is a critical challenge in computer vision, essential for enhancing image clarity in hazy conditions. Traditional methods often rely on atmospheric scattering models, while recent deep learning techniques,…
Single Image DehazingA PDE-Based Image Dehazing Method via Atmospheric Scattering Theory
This paper presents a novel partial differential equation (PDE) framework for single-image dehazing. By integrating the atmospheric scattering model with nonlocal regularization and dark channel prior, we propose the imp…
GPUImage DehazingSingle Image DehazingFine-Tuning Adversarially-Robust Transformers for Single-Image Dehazing
Single-image dehazing is an important topic in remote sensing applications, enhancing the quality of acquired images and increasing object detection precision. However, the reliability of such structures has not been suf…
Image Dehazingobject-detectionObject DetectionSingle Image DehazingSAD-Net: a full spectral self-attention detail enhancement network for single image dehazing
Single-image dehazing technology plays a significant role in video surveillance and intelligent transportation. However, existing dehazing methods using vanilla convolution only extract features in the temporal domai…
Image DehazingSingle Image DehazingDehazeMamba: SAR-guided Optical Remote Sensing Image Dehazing with Adaptive State Space Model
Optical remote sensing image dehazing presents significant challenges due to its extensive spatial scale and highly non-uniform haze distribution, which traditional single-image dehazing methods struggle to address effec…
Image DehazingSemantic SegmentationSingle Image DehazingEENet: Frequency-Aware and Spatially Multiscale Network for Single Image Dehazing
While numerous solutions leveraging convolutional neural networks and Transformers have been proposed for image dehazing, there remains significant potential to improve the balance between efficiency and reconstruction p…
DeblurringImage Defocus DeblurringImage DehazingImage Enhancement+2MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
Recent advancements in Mamba have shown promising results in image restoration. These methods typically flatten 2D images into multiple distinct 1D sequences along rows and columns, process each sequence independently us…
DeblurringDenoisingImage DeblurringImage Dehazing+6Deep Variational Bayesian Modeling of Haze Degradation Process
Relying on the representation power of neural networks, most recent works have often neglected several factors involved in haze degradation, such as transmission (the amount of light reaching an observer from a scene ove…
Image DehazingSingle Image DehazingWTCL-Dehaze: Rethinking Real-world Image Dehazing via Wavelet Transform and Contrastive Learning
Images captured in hazy outdoor conditions often suffer from colour distortion, low contrast, and loss of detail, which impair high-level vision tasks. Single image dehazing is essential for applications such as autonomo…
Autonomous DrivingContrastive LearningImage DehazingSingle Image DehazingHazeSpace2M: A Dataset for Haze Aware Single Image Dehazing
Reducing the atmospheric haze and enhancing image clarity is crucial for computer vision applications. The lack of real-life hazy ground truth images necessitates synthetic datasets, which often lack diverse haze types, …
BenchmarkingImage DehazingSingle Image DehazingSSIMSingle Image Dehazing Using Scene Depth Ordering
Images captured in hazy weather generally suffer from quality degradation, and many dehazing methods have been developed to solve this problem. However, single image dehazing problem is still challenging due to its ill-p…
Computational EfficiencyImage DehazingSingle Image DehazingScaling Up Single Image Dehazing Algorithm by Cross-Data Vision Alignment for Richer Representation Learning and Beyond
In recent years, deep neural networks tasks have increasingly relied on high-quality image inputs. With the development of high-resolution representation learning, the task of image dehazing has received significant atte…
Data AugmentationImage DehazingRepresentation LearningSingle Image DehazingHazeCLIP: Towards Language Guided Real-World Image Dehazing
Existing methods have achieved remarkable performance in image dehazing, particularly on synthetic datasets. However, they often struggle with real-world hazy images due to domain shift, limiting their practical applicab…
Image DehazingImage Quality AssessmentSingle Image DehazingHaze-Aware Attention Network for Single-Image Dehazing
Single-image dehazing is a pivotal challenge in computer vision that seeks to remove haze from images and restore clean background details. Recognizing the limitations of traditional physical model-based methods and the …
Image DehazingImage RestorationSingle Image DehazingFALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing
Image dehazing, addressing atmospheric interference like fog and haze, remains a pervasive challenge crucial for robust vision applications such as surveillance and remote sensing under adverse visibility. While various …
Autonomous DrivingImage DehazingSingle Image DehazingSSIM