  Multiple Object Tracking (MOT) has witnessed remarkable advances in recent
years. However, existing studies dominantly request prior knowledge of the
tracking target, and hence may not generalize well to unseen categories. In
contrast, Generic Multiple Object Tracking (GMOT), which requires little prior
information about the target, is largely under-explored. In this paper, we make
contributions to boost the study of GMOT in three aspects. First, we construct
the first public GMOT dataset, dubbed GMOT-40, which contains 40 carefully
annotated sequences evenly distributed among 10 object categories. In addition,
two tracking protocols are adopted to evaluate different characteristics of
tracking algorithms. Second, by noting the lack of devoted tracking algorithms,
we have designed a series of baseline GMOT algorithms. Third, we perform a
thorough evaluation on GMOT-40, involving popular MOT algorithms (with
necessary modifications) and the proposed baselines. We will release the
GMOT-40 benchmark, the evaluation results, as well as the baseline algorithm to
the public upon the publication of the paper.
