| Citation: | LI Kefu, ZHONG Huicai, GAO Xingyu, et al. Saliency guided low-light face detection[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(3): 572-584. doi: 10.13700/j.bh.1001-5965.2020.0469(in Chinese)
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To deal with the problem that it is hard for convolution neural network to do face detection in low light environment, we propose a method combining image saliency and deep learning and apply it to low-light face detection, which integrates saliency and the original RGB channels of the image into neural network training. Sufficient experiments are implemented on DARK FACE, a low-light face dataset, and the results show that the proposed low-light face detection method achieves better detection accuracy than the existing mainstream face detection algorithms on DARK FACE, thus confirming the validity of the proposed method.
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