OffsetLoss¶
- class src.loss_func.OffsetLoss(epsilon: float = 1e-05, norm=None)[source]¶
OffsetLoss Criterion computes a robust loss function based on image pixel offset. Proposed by “Zanfir et al. Deep Learning of Graph Matching. CVPR 2018.”
\[\begin{split}\mathbf{d}_i =& \sum_{j \in V_2} \left( \mathbf{S}_{i, j} P_{2j} \right)- P_{1i} \\ L_{off} =& \sum_{i \in V_1} \sqrt{||\mathbf{d}_i - \mathbf{d}^{gt}_i||^2 + \epsilon}\end{split}\]\(\mathbf{d}_i\) is the displacement vector. See
src.displacement_layer.Displacement
or more details- Parameters
epsilon – a small number for numerical stability
norm – (optional) division taken to normalize the loss
- forward(d1: torch.Tensor, d2: torch.Tensor, mask: Optional[float] = None) torch.Tensor [source]¶
- Parameters
d1 – predicted displacement matrix
d2 – ground truth displacement matrix
mask – (optional) dummy node mask
- Returns
computed offset loss
- training: bool¶