Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification
Existing vehicle re-identification methods commonly use spatial pooling operations to aggregate feature maps extracted via off-the-shelf backbone networks. They ignore exploring the spatial significance of feature maps, eventually degrading the vehicle re-identification performance.
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