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Found 8 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.
Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise
Recently, quantum classifiers have been known to be vulnerable to adversarial attacks, where quantum classifiers are fooled by imperceptible noises to have misclassification.
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.
Multi-modal Bifurcated Network for Depth Guided Image Relighting
This model extracts the image and the depth features by the bifurcated network in the encoder.
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.
