**About the Editors**

**Gee-Sern Jison Hsu** completed his dual MS degree in electrical and mechanical engineering and his Ph.D. in mechanical engineering at the University of Michigan, Ann Arbor, in 1993 and 1995, respectively. From 1995 to 1996, he was a post-doctoral fellow at the University of Michigan. From 1997 to 2000, he was a senior research staff member at the National University of Singapore. In 2001, he joined Penpower Technology, where he led research on face recognition and intelligent video surveillance. His team at Penpower Technology were recipients of the Best Innovation and Best Product Awards at the SecuTech Expo for three consecutive years. In 2007, he joined the Department of Mechanical Engineering, National Taiwan University of Science and Technology (NTUST), where he is now an associate professor. His research interests include deep learning, computer vision and pattern recognition. He serves as a reviewer for major journals, including TIP, TIFS, TCSVT, PR, CVIU and TNSRE; and major conferences, e.g., ECCV and ICME. He received best paper awards in ICMT 2011, CVGIP 2013, CVPRW 2014, ARIS 2017 and CVGIP 2018. He is a senior member of IEEE and IAPR.

**Radu Timofte** is a lecturer and research group leader at the Computer Vision Laboratory, ETH Zurich, Switzerland. He obtained a Ph.D. in Electrical Engineering at KU Leuven, Belgium, in 2013; MSc at the Univ. of Eastern Finland in 2007; and Dipl. Eng. at the Technical Univ. of Iasi, Romania, in 2006. He serves as a reviewer for top journals (such as TPAMI, TIP, IJCV, TNNLS, TCSVT, CVIU, PR) and conferences (ICCV, CVPR, ECCV, NeurIPS), and is an associate editor for *Elsevier CVIU journal* and, starting in 2020, for *IEEE Trans. PAMI* and for *SIAM Journal on Imaging Sciences*. He served as an area chair for ACCV 2018, ICCV 2019 and ECCV 2020, and as a senior PC member for IJCAI 2019 and 2020. He received a NIPS 2017 best reviewer award. His work received the best student paper award at BMVC 2019, a best scientific paper award at ICPR 2012, the best paper award at CVVT workshop (ECCV 2012), the best paper award at ChaLearn LAP workshop (ICCV 2015), the best scientific poster award at EOS 2017, the honorable mention award at FG 2017, and his team won a number of challenges, including traffic sign detection (IJCNN 2013), apparent age estimation (ICCV 2015) and real world super-resolution (ICCV 2019). He is a co-founder of Merantix and co-organizer of NTIRE, CLIC, AIM and PIRM events. His current research interests include sparse and collaborative representations, deep learning, optical flow, image/video compression, restoration and enhancement.

#### **Preface to "Deep Learning for Facial Informatics"**

Deep learning has been revolutionizing many fields in computer vision, and facial informatics is one of the major fields. Novel approaches and performance breakthroughs are often reported on existing benchmarks. As the performances on existing benchmarks are close to saturation, larger and more challenging databases are being made and considered as new benchmarks, further pushing the advancement of the technologies. Considering face recognition, for example, the VGG-Face2 and Dual-Agent GAN report nearly perfect and better-than-human performances on the IARPA Janus Benchmark A (IJB-A) benchmark. More challenging benchmarks, e.g., the IARPA Janus Benchmark C (IJB-C), QMUL-SurvFace and MegaFace, are accepted as new standards for evaluating the performance of a new approach. Such an evolution is also seen in other branches of face informatics. In this Special Issue, we have selected papers that report the latest progresses made in the following topics:


We would like to thank all of the authors who have submitted their work to this Special Issue, and the reviewers who have contributed their time for the review. We wish the readers to be able to gain some new perspectives of this interesting field. We would also like to thank MDPI for publishing this Special Issue.

> **Gee-Sern Jison Hsu, Radu Timofte** *Editors*
