Open Net-Maker opened 1 year ago
I am learning the scene part in this excellent work. But I found that the empty_space_loss in paper is like that: But in our code,it's like:
coarse_empty_space_loss = torch.zeros_like(coarse_rgb_loss) if self.penalize_empty_space > 0: depth = batch['depth'][:, None].repeat(1, _n).to(device) closer_mask = z_vals < (depth * self.opt.margin) coarse_empty_space_loss += self.empty_space_loss_fn( torch.tanh(torch.relu(out[closer_mask][:, 3])), torch.zeros_like(out[closer_mask][:, 3]) ) * self.penalize_empty_space
I am kind of confuse. could you tell me the meaning of the double activate functions? And where to correspond the formula in the paper?
I am learning the scene part in this excellent work. But I found that the empty_space_loss in paper is like that: But in our code,it's like:
I am kind of confuse. could you tell me the meaning of the double activate functions? And where to correspond the formula in the paper?