Omkar2118/datasets huggingface dataset:
AHP
Full name: Amodal Human Perception

The AHP dataset consists of 56,599 images in total which are collected from several large-scale instance segmentation and detection datasets, including COCO, VOC (w/ SBD), LIP, Objects365 and OpenImages. Each image is annotated with a pixel-level segmentation mask of a single integrated human.

The dataset is initially proposed to solve the task of human de-occlusion.
#####Data Splits

* Train: Totally 56,302 images with annotations of integrated humans.
* Valid: Totally 297 images of synthesized occlusion cases.
* Test: Totally 56 images of artificial occlusion cases.

Introducing paper: Human De-occlusion: Invisible Perception and Recovery for Humans
MISAW
Full name: MIcro-Surgical Anastomose Workflow recognition on training sessions

The MISAW data set is composed of 27 sequences of micro-surgical anastomosis on artificial blood vessels performed by 3 surgeons and 3 engineering students. The dataset contained video, kinematic, and procedural descriptions synchronized at 30Hz. The procedural descriptions contained phases, steps, and activities performed by the participants.

Source: [MIcro-Surgical Anastomose Workflow recognition challenge report](https://arxiv.org/abs/2103.13111)

Introducing paper: MIcro-Surgical Anastomose Workflow recognition challenge report