Hit 540
Subject [ICIP 2019] Attentive Layer Separation in Object Detection (by Jung Uk Kim) is accepted in IEEE ICIP2019
Date 2019-05-01
Title: Attentive Layer Separation for Object Classification and Object Localization in Object Detection

Authors: Jung Uk Kim and Yong Man Ro

Abstract: Object detection became one of the major fields in computer vision. In object detection, object classification and object localization tasks are conducted. Previous deep learning-based object detection networks perform with feature maps generated by completely shared networks. However, object classification focuses on the most discriminative object part of the feature map. Whereas, object localization requires a feature map that is focused on the entire area of the object. In this paper, we propose a novel object detection network considering the difference of two tasks. The proposed deep learning-based network mainly consists of two parts; 1) Attention network part where task-specific attention maps are generated, 2) Layer separation part where layers for estimating two tasks are separated. Comprehensive experimental results based on PASCAL VOC dataset and MS COCO da-taset showed that proposed object detection network outper-formed the state-of-the-art methods.