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2篇 您的检索式:作者名="Taijiang Mu"
    题名 作者 年代 出处 被引量
1Knowledge graph construction with structure and parameter learning for indoor scene design显示文摘We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design.We propose a novel knowledge graph framework based on the entity-relation model for representation of facts in indoor scene design, and further develop a weaklysupervised algorithm for extracting the knowledge graph representation from a small dataset using both structure and parameter learning. The proposed framework is flexible, transferable, and readable. We present a variety of computer-aided indoor scene design applications using this representation, to show the usefulness and robustness of the proposed framework.Yuan Liang Fei Xu Song-Hai Zhang Yu-Kun Lai Taijiang Mu 2018Computational Visual Media2018,4,2:3
2A Survey on Multiview Video Synthesis and Editing显示文摘Multiview video can provide more immersive perception than traditional single 2-D video. It enables both interactive free navigation applications as well as high-end autostereoscopic displays on which multiple users can perceive genuine 3-D content without glasses. The multiview format also comprises much more visual information than classical 2-D or stereo 3-D content, which makes it possible to perform various interesting editing operations both on pixel-level and object-level. This survey provides a comprehensive review of existing multiview video synthesis and editing algorithms and applications. For each topic, the related technologies in classical 2-D image and video processing are reviewed. We then continue to the discussion of recent advanced techniques for multiview video virtual view synthesis and various interactive editing applications. Due to the ongoing progress on multiview video synthesis and editing, we can foresee more and more immersive 3-D video applications will appear in the future.Shaoping Lu Taijiang Mu Songhai Zhang 2016Tsinghua Science and Technology2016,21,6:0
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