My name is Chenyang Zhu. I am a Ph.D. student in Gruvi Lab, school of Computing Science at Simon Fraser University, under the supervision of Prof. Hao(Richard) Zhang. I earned my Bachelor and Master degree in computer science from National University of Defense Technology (NUDT) in Jun. 2011 and Dec. 2013 respectively. My research interest is computer graphics with a focus on geometry processing, shape analysis and deformation.

Recent Publications

Interaction Context (ICON): Towards a Geometric Functionality Descriptor

Chenyang Zhu, Renjiao Yi, Wallace Lira, Ibraheem Alhashim, Kai Xuand Hao Zhang, "Deformation-Driven Shape Correspondence via Shape Recognition", ACM Transactions on Graphics (SIGGRAPH 2017), 36(4): 51, 2017.

Many approaches to shape comparison and recognition start by establishing a shape correspondence. We "turn the table" and show that quality shape correspondences can be obtained by performing many shape recognition tasks. What is more, the method we develop computes a fine-grained, topology-varying part correspondence between two 3D shapes where the core evaluation mechanism only recognizes shapes globally...

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Interaction Context (ICON): Towards a Geometric Functionality Descriptor

Ruizhen Hu, Chenyang Zhu, Oliver van Kaick, Ligang Liu, Ariel Shamir and Hao Zhang, "Interaction Context (ICON): Towards a Geometric Functionality Descriptor", ACM Transactions on Graphics (SIGGRAPH 2015), 33(4): 83, 2015.

We introduce a contextual descriptor which aims to provide a geometric description of the functionality of a 3D object in the context of a given scene. Differently from previous works, we do not regard functionality as an abstract label or represent it implicitly through an agent. Our descriptor, called interaction context or ICON for short, explicitly represents the geometry of object-to-object interactions...

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Organizing Heterogeneous Scene Collections through Contextual Focal Points

Kai Xu, Rui Ma, Hao Zhang, Chenyang Zhu, Ariel Shamir, Daniel Cohen-Or and Hui Huang, "Organizing Heterogeneous Scene Collections through Contextual Focal Points", ACM Transactions on Graphics (SIGGRAPH 2014), 33(4): 35, 2014.

We introduce focal points for characterizing, comparing, and organizing collections of complex and heterogeneous data and apply the concepts and algorithms developed to collections of 3D indoor scenes. We represent each scene by a graph of its constituent objects and define focal points as representative substructures in a scene collection. To organize a heterogeneous scene collection, we cluster the scenes...

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Get In Touch

  • Address

    GrUVi Lab, TASC Building 8004
    School Of Computing Science
    Simon Fraser University
    8888 University Drive
    Burnaby, B.C. V5A 1S6
    Canada
  • Email

    chenyang.chandler.zhu@gmail.com
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