자료유형 | 학위논문 |
---|---|
서명/저자사항 | A Joint Parsing System for Visual Scene Understanding. |
개인저자 | Qi, Hang. |
단체저자명 | University of California, Los Angeles. Computer Science 0201. |
발행사항 | [S.l.]: University of California, Los Angeles., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 93 p. |
기본자료 저록 | Dissertation Abstracts International 79-10B(E). Dissertation Abstract International |
ISBN | 9780438019713 |
학위논문주기 | Thesis (Ph.D.)--University of California, Los Angeles, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Song-Chun Zhu. |
요약 | The computer vision community has been long focusing on classic tasks such as object detection, human attributes classification, action recognition. While the state-of-the-art performance is getting improved every year for a wide range of tasks, |
요약 | This dissertation contains three main parts. |
요약 | Firstly, we describe a restricted visual Turing test scenario that evaluates computer vision systems across various tasks with a domain ontology and explicitly tests the grounding of concepts with formal queries. We present a benchmark for evalu |
요약 | Secondly, we propose a scalable system which leverages off-the-shelf computer vision modules to parse cross-view videos jointly. The system defines a unified knowledge representation for information sharing and is extendable to new tasks and dom |
요약 | Thirdly, we discuss a principled method to construct parse graph knowledge bases that retains rich structures and grounding details. By casting questions into graph fragments, we present a graph-matching based question-answering system that retr |
일반주제명 | Computer science. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |