The Neurips 2021 paper Searching Parameterized AP Loss for Object Detection
By Chenxin Tao,
Zizhang Li,
Xizhou Zhu,
Gao Huang,
Yong Liu,
Jifeng Dai
This is the official implementation of the Neurips 2021 paper Searching Parameterized AP Loss for Object Detection.
Introduction
TL; DR.
Parameterized AP Loss aims to better align the network training and evaluation in object detection. It builds a unified formula for classification and localization tasks via parameterized functions, where the optimal parameters are searched automatically.
Introduction.
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In evaluation of object detectors, Average Precision (AP) captures the performance of localization and classification sub-tasks simultaneously.
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In training, due to the non-differentiable nature of the