Omkar2118/datasets huggingface dataset:
YouTube-VOS 2018
Full name: Youtube Video Object Segmentation

Youtube-VOS is a Video Object Segmentation dataset that contains 4,453 videos - 3,471 for training, 474 for validation, and 508 for testing. The training and validation videos have pixel-level ground truth annotations for every 5th frame (6 fps). It also contains Instance Segmentation annotations. It has more than 7,800 unique objects, 190k high-quality manual annotations and more than 340 minutes in duration.

Source: [CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing](https://arxiv.org/abs/1910.00132)
Image Source: [https://youtube-vos.org/](https://youtube-vos.org/)

Introducing paper: YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark
TabFact
Full name: TabFact

**TabFact** is a large-scale dataset which consists of 117,854 manually annotated statements with regard to 16,573 Wikipedia tables, their relations are classified as ENTAILED and REFUTED. TabFact is the first dataset to evaluate language inference on structured data, which involves mixed reasoning skills in both symbolic and linguistic aspects. 

Source: [GitHub](https://github.com/wenhuchen/Table-Fact-Checking)

Introducing paper: TabFact: A Large-scale Dataset for Table-based Fact Verification