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Task Decoupled Knowledge Distillation For Lightweight Face Detectors

2020-10-14 · Xiaoqing Liang, Xu Zhao, Chaoyang Zhao, Nanfei Jiang, Ming Tang, Jinqiao Wang

We propose a knowledge distillation method for the face detection task. This method decouples the distillation task of face detection into two subtasks, i.e., the classification distillation subtask and the regression distillation subtask. We add the task-specific convolutions in the teacher network and add the adaption convolutions on the feature maps of the student network to generate the task decoupled features. Then, each subtask uses different samples in distilling the features to be consistent with the corresponding detection subtask. Moreover, we propose an effective probability distillation method to joint boost the accuracy of the student network.

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CASIA-IVA-Lab/TDKD pytorch

Tasks

Face DetectionKnowledge Distillationregression

Methods 이 논문이 사용한 방법론

Knowledge Distillation A very simple way to improve the performance of almost any machine learning algorithm is to train many different models on the same data and then to average their predictions.…

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