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
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri,
Renjiao Yi and Hao Zhang
, "SCORES: Shape Composition with Recursive Substructure Priors", SIGGRAPH ASIA 2018.
We introduce SCORES, a recursive neural network for shape composition. Our network takes as input sets of parts from two or more source 3D shapes and a rough initial placement of the parts. It outputs an optimized part structure for the composed shape, leading to high-quality geometry construction....
Renjiao Yi, Chenyang Zhu,
Ping Tan, Stephen Lin, "Faces as Lighting Probes via Unsupervised Deep Highlight Extraction", to appear in ECCV 2018.
We present a method for estimating detailed scene illumination using human faces in a single image. In contrast to previous works that estimate lighting in terms of low-order basis functions or distant point lights, our technique estimates illumination at a higher precision in the form of a non-parametric environment map...
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...
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...
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.