Comments (4)
Each GT H-O pair has H_box and O_box. We randomly jitter these bounding boxes, i.e. translation, changing the ratio, but making sure the IOU between these augmented boxes and the GT boxes is larger than a threshold. We then pair the augmented H_box and O_box, and regard these pairs as positive training data as well
To train the human stream, at each iteration we focus on one H-O pair. This gives us one H_box. We can also borrow 15 additional augmented H_boxes. We train the human stream with these (1+15=16) H_boxes. Thus the batch size is 16 (even though all 16 boxes are about the same H).
Please let me know if I explain the procedure clearly. Thanks.
from ican.
Thanks for your response. I have another question related to your answer, did you train the human stream with detected bounding boxes from Fast RCNN+augmented_boxes or ground truth boxes+augmented_boxes?
from ican.
Ground truth boxes+augmented boxes.
from ican.
Thank you.
from ican.
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from ican.