In this grand challenge, we focus on very challenging and realistic tasks of human-centric analysis in various crowd & complex events, including subway getting on/off, collision, fighting, and earthquake escape (cf. Figure. 1). To the best of our knowledge, few existing human analysis approaches report their performance under such complex events. With this consideration, we further propose a dataset (named as Human-in-Events or HiEve) with large-scale and densely-annotated labels covering a wide range of tasks in human-centric analysis.
Our HiEve dataset includes the currently largest number of poses (>1M), the largest number of complex-event action labels (>56k), and one of the largest number of trajectories with long terms (with average trajectory length >480). More information and details about our dataset can be found here.
Our dataset and challenge system has been re-opened to the public on August 15, 2020 as a long-term challenge. We welcome researchers to use our dataset to evaluate your research works. Please refer to How To on how to register and use our dataset.