Closed sherlockedlee closed 4 years ago
That is how L is defined - distance transform on the position of the maximum correlation response represents estimation of the target position. It would be possible to set 1 on the position of the maximum and then gradually decrease the value when going further from that position, but the network is currently trained so that there is a minimum on target position.
That is how L is defined - distance transform on the position of the maximum correlation response represents estimation of the target position. It would be possible to set 1 on the position of the maximum and then gradually decrease the value when going further from that position, but the network is currently trained so that there is a minimum on target position.
Thanks.
Thanks for your brilliant work.I have trouble understanding the refinement pathway.The input F,P focus on the object,what is the consideration of L which has higher response in the background?And it's really confusing if L has higher response in the foreground,after training,tracker behave worser than yours.