Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-identification
Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-identification
Video-based person re-identification matches video clips of people across non-overlapping cameras. Most existing methods tackle this problem by encoding each video frame in its entirety and computing an aggregate representation across all frames. In practice, people are often partially occluded, which can corrupt the extracted features. Instead, we propose a …