Computation Redistribution

Computation Redistribution is an neural architecture search method for face detection, which reallocates the computation between the backbone, neck and head of the model based on a predefined search methodology. Directly utilising the backbone of a classification network for scale-specific face detection can be sub-optimal. Therefore, network structure search is used to reallocate the computation on the backbone, neck and head, under a wide range of flop regimes. The search method is applied to RetinaNet, with ResNet as backbone, Path Aggregation Feature Pyramid Network (PAFPN) as the neck and stacked 3 × 3 convolutional layers for the head. While the general structure is simple, the total number of possible networks in the search space is unwieldy. In the first step, the authors explore the reallocation of the computation within the backbone parts (i.e. stem, C2, C3, C4, and C5), while fixing the neck and head components. Based on the optimised computation distribution on the backbone they find, they further explore the reallocation of the computation across the backbone, neck and head.