Omkar2118/datasets huggingface dataset:
LaSOT
Full name: Large-scale Single Object Tracking

LaSOT is a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame in these sequences is carefully and manually annotated with a bounding box, making LaSOT one of the largest densely annotated
tracking benchmark. The average video length of LaSOT
is more than 2,500 frames, and each sequence comprises
various challenges deriving from the wild where target objects may disappear and re-appear again in the view.

Introducing paper: LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking
TrackingNet

**TrackingNet** is a large-scale tracking dataset consisting of videos in the wild. It has a total of 30,643 videos split into 30,132 training videos and 511 testing videos, with an average of 470,9 frames.

Source: [Learning the Model Update for Siamese Trackers](https://arxiv.org/abs/1908.00855)
Image Source: [https://arxiv.org/abs/1803.10794](https://arxiv.org/abs/1803.10794)

Introducing paper: TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild