Editorial: Special Issue on Deep Learning for Face Analysis

Abstract

This special issue of the International Journal of Computer Vision (IJCV) is a compilation of papers that present new deep learning approaches for various applications on face analysis. While substantial progress has been achieved in face analysis with deep learning, many issues still remain and new problems have emerged. This special issue presents papers that have gone through the rigorous process of multiple rounds of reviewing and thus present a comprehensive account of the state-of-the art in face analysis. Submissions to the special issue closed in Spring of 2018. In total, we received 60 submissions to this special issue, of which 21 are accepted after passing the thorough reviewing process of IJCV. All submissions were reviewed by at least three reviewers. This special issue presents a snapshot of some of the best work in face analysis by deep learning,with tasks focusing on face detection, facial landmark detection, face recognition, face restoration, face synthesis, and facial expression analysis. Below is we provide a brief summary of the accepted papers by categorising them into a few key topics. Face detection remains a very active topic in the community. Thanks to the release of the WIDER Face benchmark in the year of 2016, efforts are mainly devoted to detecting faceswith awide range of scales and appearance variations in