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 RMNet backbone that was developed for fast inference. A single reidentification head from the 1/16 scale feature map outputs the 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 all queries’ Average Precision (AP) and AP is defined as an area under the precision/recall curve.
Link to performance table
name: "data" , shape: [1x3x96x48] - An input image in the format [BxCxHxW], where:
The expected color order is BGR.
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