CVOct 29, 2018

GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild

arXiv:1810.11981v31761 citations
Originality Synthesis-oriented
AI Analysis

This provides a high-diversity dataset and evaluation framework for the object tracking community, addressing limitations in existing benchmarks, but it is incremental as it builds upon prior dataset efforts.

The paper introduces GOT-10k, a large benchmark for generic object tracking with over 10,000 video segments and 1.5 million labeled bounding boxes, covering 560+ classes and 87 motion patterns, and it establishes a one-shot evaluation protocol to promote generalization in tracker development.

We introduce here a large tracking database that offers an unprecedentedly wide coverage of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon the backbone of WordNet structure and it populates the majority of over 560 classes of moving objects and 87 motion patterns, magnitudes wider than the most recent similar-scale counterparts. The contributions of this paper are summarized in the following: (1) GOT-10k offers over 10,000 video segments with more than 1.5 million manually labeled bounding boxes, enabling unified training and stable evaluation of deep trackers. (2) GOT-10k is by far the first video trajectory dataset that uses the semantic hierarchy of WordNet to guide class population. (3) For the first time, GOT-10k introduces the one-shot protocol for tracker evaluation, where the training and test classes are zero-overlapped. The protocol avoids biased evaluation results towards familiar objects and it promotes generalization in tracker development. (4) We conduct extensive tracking experiments with 39 typical tracking algorithms on GOT-10k and analyze their results in this paper. (5) Finally, we develop a comprehensive platform for the tracking community that offers full-featured evaluation toolkits, an online evaluation server, and a responsive leaderboard. The annotations of GOT-10k's test data are kept private to avoid tuning parameters on it. The database, toolkits, evaluation server and baseline results are available at http://got-10k.aitestunion.com.

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