Liangliang Nan (南亮亮)

Associate professor

3D Geoinformation Group, Faculty of Architecture and the Built Environment
Delft University of Technology (TU Delft)
Address: BG.West.550, Julianalaan 134, Delft 2628BL, Netherlands. How to get here?
E-mail: liangliang.nan AT gmail.com or liangliang.nan AT tudelft.nl

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My research interests are in 3D computer vision, computer graphics, machine learning, and 3D geoinformation, with a practical commitment to developing algorithms and tools for effectively and efficiently acquiring, analyzing, understanding, and modeling real-world scenes.

I am always looking for students who have a strong motivation in research and are interested in 3D computer vision, machine learning (especially deep learning), computer graphics, 3D geoinformation, or related fields. The selection criteria are mathematics skills (grades in mathematics courses), programming skills, and English. A nice bonus is the research experience and publication record. Please send me an email including your CV.

• Dec. 2, 2023. I am invited to serve as an area chair for ECCV 2024.

• May 1, 2023. I have been promoted to associate professor.

• Oct. 31, 2022. I am invited to serve as an area chair for ICCV 2023.

• May 1, 2022. I got tenure! This would not have been possible without the amazing support of my collaborators, colleagues, students, and friends. I am deeply grateful for your support throughout this journey.

• Nov. 29, 2021. Zhaiyu received the first prize (€3,000) in the prestigious KNVI/KIVI Thesis Awards for Computing and Information Science for his work on Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields. He was ranked No.1 among 400+ candidates. Congratulations to Zhaiyu!

• Jun. 26, 2020. Shenglan received the Best Thesis award of Geomatics for her work on Accurate, Detailed, and Automatic Modelling of Laser-Scanned Trees. Congratulations to Shenglan!

• Jun. 1, 2020. TU Delft has launched eight Artificial Intelligence Labs and I am going to lead the AI lab on 3D Urban Understanding (3DUU) together with Dr. Julian Kooij.

• Aug. 5, 2019. PolyFit (Polygonal Surface Reconstruction) is officially part of CGAL. Find more here.

• Feb. 14, 2018. Mapple now works on machines with either NVidia or AMD GPU(s)!

• Jan. 10, 2018. I joined TU Delft as a tenure-track assistant professor.

• Dec. 11, 2017. Easy3D is released. It is a lightweight, easy-to-use, and efficient C++ library for processing and rendering 3D data. Source code and details can be found here.

• Jul. 27, 2017. Paper PolyFit: Polygonal Surface Reconstruction from Point Clouds has been accepted to ICCV 2017. It provides a new theoretical foundation for piecewise planar object reconstruction. Source code, executable files, and data are available on the project page.

• Jul. 25, 2016. Paper Block Assembly for Global Registration of Building Scans has been accepted to SIGGRAPH Asia 2016.

• Jul. 12, 2016. Two papers were accepted to ECCV. One is about Manhattan world scene reconstruction and the other is about urban asset extraction from wild images.

• Aug. 30, 2015. Our CAD/Graphics 2015 paper Reconstructing Building Mass Models from UAV images won the Best Paper Award.

• Jan. 14, 2015. Paper Template Assembly for Detailed Urban Reconstruction has been accepted to Eurographics 2015.

• Aug. 31, 2014. Paper 2D-3D Lifting for Shape Reconstruction" has been accepted to Pacific Graphics 2014.

• May. 27, 2013. I joined the Visual Computing Center at KAUST as a research scientist.

• Dec. 14, 2012. I received the Lu Zengyong CAD&CG High-Tech Award (2nd place).

• Aug. 6, 2012. Our paper A Search-Classify Approach for Cluttered Indoor Scene Understanding has been accepted to SIGGRAPH Asia 2012.

• Apr. 26, 2011. I am awarded the K.C.Wong Post-doctoral Fellowship of the Chinese Academy of Sciences.