Omkar2118/datasets huggingface dataset:
UMIST

The Sheffield (previously **UMIST**) Face Database consists of 564 images of 20 individuals (mixed race/gender/appearance). Each individual is shown in a range of poses from profile to frontal views – each in a separate directory labelled 1a, 1b, … 1t and images are numbered consecutively as they were taken. The files are all in PGM format, approximately 220 x 220 pixels with 256-bit grey-scale.

Source: [https://www.visioneng.org.uk/datasets/](https://www.visioneng.org.uk/datasets/)
Image Source: [https://www.visioneng.org.uk/datasets/](https://www.visioneng.org.uk/datasets/)
I-HAZE

The I-Haze dataset contains 25 indoor hazy images (size 2833×4657 pixels) training. It has 5 hazy images for validation along with their corresponding ground truth images.

Source: [Single image dehazing for a variety of haze scenarios using back projected pyramid network](https://arxiv.org/abs/2008.06713)
Image Source: [https://data.vision.ee.ethz.ch/cvl/ntire18//i-haze/](https://data.vision.ee.ethz.ch/cvl/ntire18//i-haze/)

Introducing paper: I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images
SHREC
Full name: SHape REtrieval Contest

The **SHREC** dataset contains 14 dynamic gestures performed by 28 participants (all participants are right handed) and captured by the Intel RealSense short range depth camera. Each gesture is performed between 1 and 10 times by each participant in two way: using one finger and the whole hand. Therefore, the dataset is composed by 2800 sequences captured. The depth image, with a resolution of 640x480, and the coordinates of 22 joints (both in the 2D depth image space and in the 3D world space) are saved for each frame of each sequence in the dataset.

Source: [Exploiting Recurrent Neural Networks and Leap Motion Controller for Sign Language and Semaphoric Gesture Recognition](https://arxiv.org/abs/1803.10435)
Image Source: [http://tosca.cs.technion.ac.il/book/shrec.html](http://tosca.cs.technion.ac.il/book/shrec.html)

Introducing paper: A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries