Face detector based on SqueezeNet light (half-channels) as a backbone with a single SSD for indoor/outdoor scenes shot by a front-facing camera. The backbone consists of fire modules to reduce the number of computations. The single SSD head from 1/16 scale feature map has nine clustered prior boxes.
Average Precision (AP) is defined as an area under the precision/recall curve. All numbers were evaluated by taking into account only faces bigger than 60 x 60 pixels.
1, 3, 300, 300 in the format
B, C, H, W, where:
B- batch size
C- number of channels
H- image height
W- image width
Expected color order:
The net outputs blob with shape:
1, 1, 200, 7 in the format
1, 1, N, 7, where
N is the number of detected bounding boxes. Each detection has the format [
image_id- ID of the image in the batch
label- predicted class ID (1 - face)
conf- confidence for the predicted class
y_min) - coordinates of the top left bounding box corner
y_max) - coordinates of the bottom right bounding box corner
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