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AATTCT-IDS
A benchmark Abdominal Adipose Tissue CT Image Dataset (AATTCT-IDS) for image denoising, semantic segmentation, and radiomics evaluation. -
DND dataset
The DND dataset contains ∼1000 pairs of clean and noisy images of consumer cameras. -
SIDD dataset
The SIDD dataset contains ∼1000 pairs of clean and noisy images of smartphone cameras. -
AbdomenCT-1K dataset
The AbdomenCT-1K dataset comprises more than 1000 abdominal CT scans aggregated from 6 existing datasets. -
Chalearn LAP In-painting Competition Track 3 - Fingerprint Denoising and In-p...
The dataset provided by the organizers consisted of 84000 (200, 400) fingerprint images generated using Anguli: Synthetic Fingerprint Generator. Those images were then... -
NTIRE2019 Real Image Denoising Challenge - Track 2:sRGB
The dataset used for training and validation in the NTIRE2019 Real Image Denoising Challenge - Track 2:sRGB. -
SIDD and DND
Real-world image denoising dataset (SIDD) and Darmstadt noise dataset (DND) are used for training and validation. -
A non-local algorithm for image denoising
A non-local algorithm for image denoising. -
Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise...
Multiplicative noise widely exists in radar images, medical images and other important fields' images. The removal of multiplicative noise can help the application of various... -
CIFAR-10, ImageNet and CelebA dataset
The dataset used in this paper is the CIFAR-10, ImageNet and CelebA dataset. -
CBSD500 dataset
The dataset used in the paper is a benchmark dataset for image denoising tasks. -
KOdak dataset and CSet9 dataset
The dataset used in the paper is a benchmark dataset for image denoising tasks.