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About Joint Face Detention & Alignment Using Multitask Cascaded Convolutional Networks
This document summarizes a research paper on joint face detection and alignment using multi-task cascaded convolutional networks. The proposed framework uses a cascaded structure with three stages of convolutional neural networks to detect faces and landmarks in a coarse-to-fine manner. It also introduces an online hard sample mining strategy to automatically improve performance during training without manual sample selection. Experimental results show the method achieves state-of-the-art accuracy on benchmarks for face detection and alignment, while maintaining real-time performance.
Detailed Information
| Author: | ['Mohamed Nofal'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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