DSEC-MOT: an Event-based MOT Dataset

Introduction Welcome to the new challenging event-based multi-object tracking dataset (DSEC-MOT) repository. Our goal is to provide a challenging and diverse event-based MOT dataset with various real-world scenarios to facilitate the objective and comphrehensive evaluation of event-based multi-object tracking algorithms. This dataset, built upon DSEC(https://dsec.ifi.uzh.ch/), contains a variety of traffic entities and complex scenarios, aiming to address the current lack of event-based MOT datasets. Dataset Statistics DSEC-MOT contains: - 12 annotated sequences with a total of 37,080 boxes, 502 tracks, and 769.2-second duration - 7 object classes including cars, pedestrians, bicycles, motorcycles, buses, trucks, and trains - Challenging scenarios including crowded urban areas and rural scenes with various lighting conditions - Severe occlusions, making the dataset suitable for testing trackers' occlusion handling capabilities - Event resolution 640 x 480