Object bounding box-critic networks for occlusion-robust object detection in road scene도로 장면에서 오클루전에 강인한 객체 검출을 위한 객체 영역-비평 네트워크

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dc.contributor.advisorRo, Yong Man-
dc.contributor.advisor노용만-
dc.contributor.authorKim, Jung Uk-
dc.date.accessioned2019-09-04T02:41:16Z-
dc.date.available2019-09-04T02:41:16Z-
dc.date.issued2018-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=733999&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/266763-
dc.description학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2018.2,[iii, 19 p. :]-
dc.description.abstractObject detection in a road scene has received a significant interest in the research field of developing autonomous vehicles and automatic road monitoring systems. However, object occlusion problems frequently happen in generic road scene. Due to the occlusion problem, previous object detection methods have limitations that they could not detect objects correctly. In this thesis, we propose a novel object detection network aiming to an occlusion robust method. To effectively detect object even in occlusion cases, the proposed network mainly consists of two parts-
dc.description.abstract1) Object bounding box (OBB)-critic network which handle occlusion early at feature map encoded from input image. 2) RoI object bounding box-critic network which handle occlusion at the RoI feature predicted in the Region Proposal Network (RPN). Two OBB-critic networks are trained by an adversarial learning. Comprehensive experimental results on a KITTI dataset showed that the proposed object detection network outperformed state-of-the-art object detection methods.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectObject Detection▼aAdversarial Network▼aObject Bounding Box▼aCritic Network▼aOcclusion-
dc.subject객체 검출▼a적대적 학습▼a객체 영역▼a비평 네트워크▼a오클루전-
dc.titleObject bounding box-critic networks for occlusion-robust object detection in road scene-
dc.title.alternative도로 장면에서 오클루전에 강인한 객체 검출을 위한 객체 영역-비평 네트워크-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :전기및전자공학부,-
dc.contributor.alternativeauthor김정욱-
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