We are an inter-disciplinary team of researchers working in visual computing, in particular, computer graphics and computer vision. Current areas of focus include 3D and robotic vision, 3D printing and content creation, animation, AR/VR, geometric and image-based modelling, machine learning, natural phenomenon, and shape analysis. Our research works frequently appear in top venues such as SIGGRAPH, CVPR, and ICCV (we rank #13 in the world in terms of top publications in visual computing, as of 10/2017) and we collaborate widely with the industry and academia (e.g., Adobe Research, Google, MSRA, Princeton, Stanford, and Washington). Our faculty and students have won numerous honours and awards, including FRSC, Alain Fournier Best Thesis Award, Google Faculty Award, TR35@Singapore, NSERC Discovery Accelerator, and six best paper awards from ECCV, SCA, SGP, etc. Gruvi alumni went on to take up faculty positions in Canada, the US, and Asia, while others now work at companies including Apple, EA, Facebook, Google, IBM, and Microsoft.
October 13, 2017
GrUVi members co-author two technical papers: “Learning to Predict Part Mobility from a Single Static Snapshot” and “Learning to Group Discrete Graphical Patterns”; and one course at SIGGRAPH Asia 2017, to be held in Bangkok, Thailand, November 27-30. At ICCV 2017, three papers co-authored by GrUVi members have been presented.
October 1, 2017
GrUVi faculty Yasu Furukawa will be a program co-chair for 3DV 2017, which will be held in Qingdao, China between October 10 and 12. Richard Zhang will also be a program co-chair for Computer Graphics International (CGI) 2018, which will be hosted at Bintan Island, Indonesia, June 11-14, 2018.
August 27, 2017
The paper “An Exquisite Corpse Tool for Collaborative 3D Shape Design”, co-authored by Warunika, Parmit Chilana, Daniel Cohen-Or, and Richard Zhang won a best paper award at the recent CAD/Graphics conference. This work was part of Warunika’s MSc thesis; she graduated in Dec 2016 and is now at IBM.
August 26, 2017
The paper “Generative Recursive Autoencoder for Shape Structures (GRASS)” co-authored by Prof. Richard Zhang and former GrUVi member Kai Xu, was selected as one of the six technical papers from SIGGRAPH 2017 for press release. See the press release article here and an invited article by Richard Zhang on SFU’s official website.