网(多面体)
面子(社会学概念)
人脸检测
面部识别系统
计算机科学
人工智能
模式识别(心理学)
数学
社会学
几何学
社会科学
作者
Lei Pang,Yue Ming,Li Chao
出处
期刊:International Conference on Signal Processing
日期:2018-08-01
被引量:4
标识
DOI:10.1109/icsp.2018.8652436
摘要
The face multi-task analysis is high-profile in recent years. Face detection and recognition are more challenging in one net. We present a new parallel network architecture for two face tasks in one net, achieving end-to-end face detection and recognition. Firstly, we train a better face detection network. Then, the selection of the shared layers has a signification impact on the result in speed and accuracy for recognition, so we determine the optimal shared layers by experiments. Finally, shared layers contains discriminative information for face recognition, and we put the recognition network under the shared layer of the detection network. We achieve parallel end-to-end face detection and recognition in one net, comprehensively evaluated this method on several face detection and recognition benchmark datasets, including the Labeled Faces in the Wild (LFW) and Face Detection Datasets and Benchmark (FDDB). We get better detection and recognition accuracy on LFW and FDDB, and achieve faster speed compared to other methods. Our results demonstrate the effectiveness of the proposed approach.
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