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  • title: Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors
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            Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors
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            Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors

            May 3, 2021

            Speakers

            LZ

            Linfeng Zhang

            Speaker · 0 followers

            KM

            Kaisheng Ma

            Speaker · 0 followers

            About

            Knowledge distillation, in which a student model is trained to mimic a teacher model, has been proved as an effective technique for model compression and model accuracy boosting. However, most knowledge distillation methods, designed for image classification, have failed on more challenging tasks, such as object detection. In this paper, we suggest that the failure of knowledge distillation on object detection is mainly caused by two reasons: (1) the imbalance between pixels of foreground and ba…

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            I2

            ICLR 2021

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            The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning. ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

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