hi,how to fix the problem that one pix belong to more than one class and these class belong to the same feature map?

[gybuaa]

Thanks for yours great job! According to the paper,we will just delete the sample with maximal area.And, the multi-level prediction can largely alleviate the problem.But how to fix the problem if one pix belong to more than one class and these classes belong to the same level feature map,and their area are the same？

[tianzhi0549]

@gybuaa I think very few boxes are in this case. Just choose a random one in the case, which would not affect the final performance.

[gybuaa]

@gybuaa I think very few boxes are in this case. Just choose a random one in the case, which would not affect the final performance. Thanks a lot ！ may i ask if we want to avoid this problem absolutely,do you have any idea or research direction for me? thanks again for your reply！