A coupled encoder–decoder network for joint face detection and landmark localization
| Autor: | Dimitris N. Metaxas, Xiang Yu, Thirimachos Bourlai, Lezi Wang |
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| Rok vydání: | 2019 |
| Předmět: |
Landmark
Computer science business.industry 020207 software engineering 02 engineering and technology Facial recognition system Robustness (computer science) Signal Processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Computer Vision and Pattern Recognition Encoder decoder Artificial intelligence Face detection business Encoder |
| Zdroj: | Image and Vision Computing. 87:37-46 |
| ISSN: | 0262-8856 |
| DOI: | 10.1016/j.imavis.2018.09.008 |
| Popis: | Face detection and landmark localization have been extensively investigated and are the prerequisite for many face related applications, such as face recognition and 3D face reconstruction. Most existing methods address only one of the two problems. In this paper, we propose a coupled encoder–decoder network to jointly detect faces and localize facial key points. The encoder and decoder generate response maps for facial landmark localization. Moreover, we observe that the intermediate feature maps from the encoder and decoder represent facial regions, which motivates us to build a unified framework for multi-scale cascaded face detection by coupling the feature maps. Experiments on face detection using two public benchmarks show improved results compared to the existing methods. They also demonstrate that face detection as a pre-processing step leads to increased robustness in face recognition. Finally, our experiments show that the landmark localization accuracy is consistently better than the state-of-the-art on three face-in-the-wild databases. |
| Databáze: | OpenAIRE |
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