Person re-identification (Re-ID) aims to retrieve a person of interest across multiple nonoverlapping cameras. In recent years, to enable person Re-ID technology to play out its application value in real-world scenarios, visual surveillance through unmanned aerial vehicle (UAV) platforms has received intense attention, and aerial person datasets have been constructed. However, the pedestrian images captured by ground cameras and those captured by UAVs exhibit great differences. Person Re-ID methods based on ground person images have difficulty performing Re-ID on aerial person images. In this paper, we first use a meta-transfer method to learn to gener-aerial imagery, meta-transfer learning, person re-identification
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