Welcome to Rui Ma's homepage
About me
My name is Rui Ma (马锐). I recieved my Ph.D. in Computer Science in September 2017, from School of Computing Science, Simon Fraser University, Canada. I worked in the GrUVi Lab under the supervision of Prof. Hao (Richard) Zhang for my PhD study during 2012 to 2017. Before that, I obtained my M.Sc. and B.Sc. both in Computational Mathmatics from Jilin University, China. My research interests include computer graphics, high-level geometry processing, shape analysis and 3D indoor scene modeling.

Email: ruim@sfu.ca

Rui Ma, Honghua Li, Changqing Zou, Zicheng Liao, Xin Tong and Hao Zhang.
"Action-Driven 3D Indoor Scene Evolution".
ACM Transactions on Graphics (SIGGRAPH Asia 2016), 35(6).

We introduce a framework for action-driven evolution of 3D indoor scenes, where the goal is to simulate how scenes are altered by human actions, and specifically, by object placements necessitated by the actions.

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

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.

Ibraheem Alhashim, Honghua Li, Kai Xu, Junjie Cao, Rui Ma and Hao Zhang.
"Topology-Varying 3D Shape Creation via Structural Blending".
ACM Transactions on Graphics (SIGGRAPH 2014), 33(4).

We introduce an algorithm for generating novel 3D models via topology-varying shape blending. Given two shapes with different topology, our method blends them topologically and geometrically, producing continuous series of in-betweens representing new creations.

Rui Ma
"Analysis and Modeling of 3D Indoor Scenes".
SFU Depth Examination Report, 2017 Summer.

This report surveys the recent research progress in graphics on geometry, structure and semantic analysis of 3D indoor data and different modeling techniques for creating plausible and realistic indoor scenes.