Comments (3)
tgc1997
commented on August 18, 2024
Hi, we use the position (4 dims) and the area (1 dim) of the region as spatial feature
At2021-07-26 17:08:52，Arnav ***@***.***:
Hi,
I see you using the 2D CNN features (1536 dim), 3D CNN features (1024 dim), RCNN features (2048 dim). I also see something called spatial features of 5 dimensions. What are these features? I could not find them mentioned anywhere in the paper?
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arnavc1712
commented on August 18, 2024
@tgc1997,
Thank you!
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tgc1997
commented on August 18, 2024
we use the following code for normalization:
def _boxes2sfeat(boxes, im):
S_H = im.shape[0]
S_W = im.shape[1]
S_A = S_W * S_H
boxes = np.asarray(boxes)
# calculate sfeat
x1 = boxes[:, 0]
y1 = boxes[:, 1]
x2 = boxes[:, 2]
y2 = boxes[:, 3]
Sa = (x2 - x1) * (y2 - y1)
sfeat = np.hstack(((x1/S_W)[:, np.newaxis],
(y1/S_H)[:, np.newaxis],
(x2/S_W)[:, np.newaxis],
(y2/S_H)[:, np.newaxis],
(Sa/S_A)[:, np.newaxis]))
return sfeatfrom rmn.
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