So i used the MobileNetV3 architecture to train an object detector with heat maps instead of bounding boxes.
I didn’t change anything in the MobileNetV3 arch except raising the number of output neurons to 2704 so it can be resized to 52x52 image with a sigmoid activation function , this should enable me to subtract the heat maps from the output with MSE loss function and get a good results from the model.
The problem that this doesn’t happen and after some research i found out that i need to give weights for the background pixels less than the foreground ones and my question how i can do something like this ?
And if someone tried training with heatmaps, is my configuration good or there is something better ?