UAV-Human is a large dataset for human behavior understanding with UAVs. It contains 67,428 multi-modal video sequences and 119 subjects for action recognition, 22,476 frames for pose estimation, 41,290 frames and 1,144 identities for person re-identification, and 22,263 frames for attribute recognition. The dataset was collected by a flying UAV in multiple urban and rural districts in both daytime and nighttime over three months, hence covering extensive diversities w.r.t subjects, backgrounds, illuminations, weathers, occlusions, camera motions, and UAV flying attitudes. This dataset can be used for UAV-based human behavior understanding, including action recognition, pose estimation, re-identification, and attribute recognition.
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FreeMan is the first large-scale multi-view human motion dataset under real scenarios. FreeMan was captured by synchro- nizing 8 smartphones across diverse scenarios. It comprises 11M frames from 8000 sequences, viewed from different perspectives. These sequences cover 40 subjects across 10 different scenarios, each with varying lighting conditions.
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