Title: Teaching a Computer to be an Architect
Abstract: I will present our recent work on structured geometry reconstruction and generation, which help architects with their workflows. For reconstruction, I will talk about vector floorplan reconstruction from scanned floorplan images or RGBD images acquired on-site: What the key insights were and how we changed the landscape of floorplan reconstruction in the last 5 years. For generation, I will talk about the graph-constrained floorplan generation work (House-GAN): How we fused a reconstruction technique with GAN to build the system. Lastly, I will share my views on how the relationships of structured reconstruction and generation (two once very distant fields) are changing recently.
Bio: Dr. Yasutaka Furukawa is an associate professor in the School of Computing Science at Simon Fraser University (SFU). Dr. Furukawa's group has made fundamental and practical contributions to 3D reconstruction algorithms, improved localization techniques, and computational architectural modeling. Their open-source software has been widely adopted by tech companies used in surprising applications such as 3D printing of turtle shells and archaeological reconstruction. Dr. Furukawa received the best student paper award at ECCV 2012, the NSF CAREER Award in 2015, CS-CAN Outstanding Young CS Researcher Award 2018, Google Faculty Research Awards in 2016, 2017, and 2018, and PAMI Longuet-Higgins prize in 2020.