Pedestrian detection network based on SSD framework with tuned MobileNet v1 as a feature extractor.
Metric | Value |
---|---|
Average Precision (AP) | 88% |
Target pedestrian size | 60 x 120 pixels on Full HD image |
Max objects to detect | 200 |
GFlops | 2.836 |
MParams | 1.165 |
Source framework | Caffe* |
Average Precision metric described in: Mark Everingham et al. “The PASCAL Visual Object Classes (VOC) Challenge”.
Tested on an internal dataset with 1001 pedestrian to detect.
Link to performance table
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