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Hi,
Say i have a region proposal with co-ordinates (top left, bottom right coordinates): (0, 3), (7, 8) and the output i am taking out after roi pooling is 2x2. So, according to the roi pooling code in this repo, we create 4 regions of size([height,width]) [floor(7/2), floor(5/2)],i.e,[3,2]. But in this case, the four regions of size [3,2] would cover only [6,4] area of the region proposal and the features from the rest of the proposal gets ignored.
Here, the first box has size [3,2] while the rest of the boxes inside the proposal regions have their sizes adjusted so as to cover and extract features from the entire proposal region.
So, wouldnt the approach mentioned in the above blog be better or is that somehow being ensured in your implementation?
The text was updated successfully, but these errors were encountered:
Hi,
Say i have a region proposal with co-ordinates (top left, bottom right coordinates): (0, 3), (7, 8) and the output i am taking out after roi pooling is 2x2. So, according to the roi pooling code in this repo, we create 4 regions of size([height,width]) [floor(7/2), floor(5/2)],i.e,[3,2]. But in this case, the four regions of size [3,2] would cover only [6,4] area of the region proposal and the features from the rest of the proposal gets ignored.
I came across this blog: https://deepsense.ai/region-of-interest-pooling-explained/ where they select regions like below
Here, the first box has size [3,2] while the rest of the boxes inside the proposal regions have their sizes adjusted so as to cover and extract features from the entire proposal region.
So, wouldnt the approach mentioned in the above blog be better or is that somehow being ensured in your implementation?
The text was updated successfully, but these errors were encountered: