Omkar2118/datasets huggingface dataset:
MOET

**MOET** a dataset consists of gaze data from participants tracking specific objects, annotated with labels and bounding boxes, in crowded real-world videos, for training and evaluating attention decoding algorithms.

Source:[Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models](https://arxiv.org/pdf/2211.10966v1.pdf)

Image Source: [https://arxiv.org/pdf/2211.10966v1.pdf](https://arxiv.org/pdf/2211.10966v1.pdf)

Introducing paper: Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models
CORSMAL

**CORSMAL** is a dataset for estimating the position and orientation in 3D (or 6D pose) of an object from a single view. The dataset consists of 138,240 images of rendered hands and forearms holding 48 synthetic objects, split into 3 grasp categories over 30 real backgrounds.

Source: [A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers](https://arxiv.org/pdf/2211.10470v1.pdf)

Image Source: [https://arxiv.org/pdf/2211.10470v1.pdf](https://arxiv.org/pdf/2211.10470v1.pdf)

Introducing paper: A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers