@inproceedings{71cbf55a574b4576a3b8990452512a5f,
title = "Deep Learning-Based Facial Landmarks Localization with Loss Comparison",
abstract = "Facial landmarks localization has widespread use in various facial analysis applications which can solve major problems in the computer vision field. Localizing the key points such as eye corners, eye centers, nose center, jawline, etc gives the vital information needed for analysis of face status like expressions, health conditions, etc. The paper addresses a deep learning-based facial landmarks localization approach. MobileNet V3 is used to predict the facial landmarks on human faces which are mapped on the detected face in real-time. The model is evaluated with the wing and adaptive wing loss functions. The detector is examined with various head poses and occlusion conditions.",
keywords = "Adaptive wing loss, Facial landmarks, Facial landmarks localization, MobileNet, Wing loss",
author = "Savina Colaco and Han, {Dong Seog}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 11th International Conference on Information and Communication Technology Convergence, ICTC 2020 ; Conference date: 21-10-2020 Through 23-10-2020",
year = "2020",
month = oct,
day = "21",
doi = "10.1109/ICTC49870.2020.9289429",
language = "English",
series = "International Conference on ICT Convergence",
publisher = "IEEE Computer Society",
pages = "584--587",
booktitle = "ICTC 2020 - 11th International Conference on ICT Convergence",
address = "United States",
}
