STEdge: Self-training Edge Detection with Multi-layer Teaching and Regularization. (arXiv:2201.05121v1 [cs.CV])

Learning-based edge detection has hereunto been strongly supervised with
pixel-wise annotations which are tedious to obtain manually. We study the
problem of self-training edge detection, leveraging the untapped wealth of
large-scale unlabeled image datasets. We design a self-supervised framework
with multi-layer regularization and self-teaching. In particular, we impose a
consistency regularization which enforces the outputs from each of the multiple
layers to be consistent for the input image and its perturbed counterpart. We
adopt L0-smoothing as the 'perturbation' to encourage …

arxiv cv detection edge teaching training