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Found 10 papers, 7 papers with code
JSTASR: Joint Size and Transparency-Aware Snow Removal Algorithm Based on Modified Partial Convolution and Veiling Effect Removal
It can classify snow particles according to their sizes and conduct snow removal in different scales.
RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning
Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision.
Learning Multiple Adverse Weather Removal via Two-Stage Knowledge Learning and Multi-Contrastive Regularization: Toward a Unified Model
At the KC, the student network aims to learn the comprehensive bad weather removal problem from multiple well-trained teacher networks where each of them is specialized in a specific bad weather removal problem.
ContourletNet: A Generalized Rain Removal Architecture Using Multi-Direction Hierarchical Representation
The rainy scenarios can be categorized into two classes: moderate rain and heavy rain scenes.
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss
Moreover, due to the limitation of existing snow datasets, to simulate the snow scenarios comprehensively, we propose a large-scale dataset called Comprehensive Snow Dataset (CSD).
PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal
In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.
Occluded Face Recognition Using Low-rank Regression with Generalized Gradient Direction
In this paper, a very effective method to solve the contiguous face occlusion recognition problem is proposed.
Nonconvex Approach for Sparse and Low-Rank Constrained Models with Dual Momentum
We first propose a novel nonconvex rank surrogate on the general rank minimization problem and apply this to the corrupted image completion problem.
Discrete Gyrator Transforms: Computational Algorithms and Applications
Besides, we propose a kind of DGT based on the eigenfunctions of the gyrator transform.
Blur Kernel Estimation Using Normalized Color-Line Prior
The intermediate patches can then guide the estimation of the blur kernel.
