A Coupled Encoder-Decoder Network for Joint Face Detection and Landmark Localization
| Autor: | Lezi Wang, Dimitris N. Metaxas, Xiang Yu |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Landmark
business.industry Computer science 02 engineering and technology 021001 nanoscience & nanotechnology Facial recognition system Object-class detection Feature (computer vision) Face (geometry) 0202 electrical engineering electronic engineering information engineering Three-dimensional face recognition 020201 artificial intelligence & image processing Computer vision Artificial intelligence 0210 nano-technology business Face detection Encoder |
| Zdroj: | FG |
| DOI: | 10.1109/fg.2017.40 |
| Popis: | Face detection and landmark localization have been extensively investigated and are the prerequisite for many face applications, such as face recognition and 3D face reconstruction. Most existing methods achieve success on only one of the two problems. In this paper, we propose a coupled encoderdecoder 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 have strong power in describing facial regions, which motivates us to build a unified framework by coupling the feature maps for multi-scale cascaded face detection. Experiments on face detection show strongly competitive results against the existing methods on two public benchmarks. The landmark localization further shows consistently better accuracy than state-of-the-arts on three face-in-the-wild databases. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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