TATL: Task Agnostic Transfer Learning for Skin Attributes Detection. (arXiv:2104.01641v2 [cs.CV] UPDATED)

Web: http://arxiv.org/abs/2104.01641

Existing skin attributes detection methods usually initialize with a
pre-trained Imagenet network and then fine-tune on a medical target task.
However, we argue that such approaches are suboptimal because medical datasets
are largely different from ImageNet and often contain limited training samples.
In this work, we propose \emph{Task Agnostic Transfer Learning (TATL)}, a novel
framework motivated by dermatologists' behaviors in the skincare context. TATL
learns an attribute-agnostic segmenter that detects lesion skin regions and
then transfers this knowledge to a …

arxiv cv detection learning transfer learning