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Dec, 2022
通过随机温度缩放提高人脸识别模型的训练和推理效果
Improving Training and Inference of Face Recognition Models via Random Temperature Scaling
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Lei Shang, Mouxiao Huang, Wu Shi, Yuchen Liu, Yang Liu...
TL;DR
通过概率视角和随机温度缩放的统一框架,提出一种可靠的脸部识别算法,可用于不确定、低质量和甚至是分布外的图像检测,具有较高的准确性和稳定性。
Abstract
Data uncertainty is commonly observed in the images for
face recognition
(FR). However,
deep learning
algorithms often make predictions with high confidence even for uncertain or irrelevant inputs. Intuitively, F
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