This is a person reidentification model for a general scenario. It uses a whole body image as an input and outputs an embedding vector to match a pair of images by the cosine distance. The model is based on the RMNet backbone developed for fast inference. A single reidentification head from the 1/16 scale feature map outputs an embedding vector of 256 floats.
|Market-1501 rank@1 accuracy||0.7791|
|Pose coverage||Standing upright, parallel to image plane|
|Support of occluded pedestrians||YES|
The cumulative matching curve (CMC) at rank-1 is accuracy denoting the possibility to locate at least one true positive in the top-1 rank. Mean Average Precision (mAP) is the mean across Average Precision (AP) of all queries. AP is defined as the area under the precision and recall curve.
data , shape: [1x3x96x48]. An input image in the format [BxCxHxW], where:
The expected color order is BGR.
descriptor, which can be compared with other descriptors using the cosine distance.
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