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RESIDE SOTS
The dataset used for training and testing the pyramid fusion dark channel prior (PF-DCP) algorithm for single image dehazing. -
Contrastive learning for compact single image dehazing
Contrastive learning for compact single image dehazing -
From synthetic to real: Image dehazing collaborating with unlabeled real data
From synthetic to real: Image dehazing collaborating with unlabeled real data -
Benchmarking single-image dehazing and beyond
Benchmarking single-image dehazing and beyond -
DEA-Net: Single image dehazing based on detail-enhanced convolution and conte...
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. -
Hazy-COCO dataset
The Hazy-COCO dataset is a synthetic dataset generated by adding haze to the MS COCO dataset. -
REalistic Single Image DEhazing (RESIDE) dataset
The RESIDE dataset is a large-scale dataset for benchmarking single image dehazing algorithms, and it includes both indoor and outdoor hazy images. -
Custom Dataset
The authors created a custom dataset for their experiment, consisting of 33,000 images of 320 possible object-image combinations, with 10 possible shapes, 8 possible colors, 2... -
Synthetic Dataset
The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs...