A large, high-diversity, one-shot database for generic object tracking in the wild

Key Features

• Large-Scale
  The dataset contains more than 10,000 video segments of real-world moving objects and over 1.5 million manually labeled bounding boxes.
• Generic Classes
  The dataset is backboned by WordNet and it covers a majority of 560+ classes of real-world moving objects and 80+ classes of motion patterns.
• One-Shot
  The dataset encourages the development of generic purposed trackers by following the one-shot rule that object classes between train and test sets are zero-overlapped.
• Unified Training Data
  The fair comparison of deep trackers is ensured with the protocol that all approaches are using the same training data provided by the dataset.
• Extra Labeling
  The dataset provides extra labels including object visible ratios and motion classes as additional supervision for handling specific challenges.
• Efficient Evaluation
  The test set embodies 84 object classes and 32 motion classes with only 180 video segments, allowing for efficient evaluation.

Paper

Please cite this paper if GOT-10k helps your research. [PDF] [BibTex]]