相关数据集
MIT-Adobe FiveK 图像增强数据集
MIT-Adobe FiveK 包含 5,000 张 RAW 格式的照片，由不同的摄影师用 SLR 相机拍摄。这些照片涵盖广泛的场景、主体和照明条件。
超神经2022-10-10 更新810
Discriminatory ability of the blur features.
U = Mann-Whitney statistic, m = n = blur and sharp sample sizes. ALL = complete training set (m = n = 24,000); HE = HE training set (m = n = 8,000); IHC = IHC training set (m = n
NIAID Data Ecosystem80
The layers for DnCNN model.
Ambient lighting conditions play a crucial role in determining the perceptual quality of images from photographic devices. In general, inadequate transmission light and undesired atmospheric condition
NIAID Data Ecosystem50
MRASN dataset
We provided a new set of extreme low-light datasets of short exposure raw images in RGB format and long-exposure reference images of the same scenes.
DataCite Commons2022-03-07 更新120
bitmind/MS-COCO-unique-256_training_faces
--- dataset_info: - config_name: base_transforms features: - name: image dtype: image - name: original_index dtype: int64 - name: landmark sequence: sequence: int64 - name:
Hugging Face2024-09-18 更新60
