Daxuan (č¾¾č±) Ren (ä»»)
Ph.D Student at Nanyang Technological University, Singapore
- NTU School of Computer Science and Engineering (SCSE)
- Principal Software Engineer @ Autodesk
- Ex-Algorithm Researcher @ SenseTime Research
- Ex-Sensetime-NTU Industrial Post-Graduate Program (IPP)
- Email: daxuan001 [at] e.ntu.edu.sg
I am currently a Principal Software Development Engineer at Autodesk and a Ph.D. student in the College of Computing and Data Science at Nanyang Technological University (NTU), Singapore. I am supervised by Prof. Zheng Jianmin (NTU) and Prof. Cai Jianfei (Monash University). I was previously part of the Indistrial Post-Graduate Program (IPP), a joint initiative between SenseTime and NTU under the Singapore Economic Development Board (EDB).
I received my bachelor degree in Computer Science from NTU in 2018. During my undergraduate study, I was interested in High-Performance-Computing(HPC) and privileged to represented NTU to compete with other top universities around the globe in the International Supercomputer Conference (ISC) Student Cluster Competetion in Frankfurt, Germany, and ACM/IEEE Supercomputer Conference (SC) Student Cluster Competetion in Salt Lake City, USA.
Prior to my Ph.D, I was a software engineer in Autodesk working on large-scale 3D Reconstruction Engine (Autodesk ReCap Photo) including Structure-from-Motion (SFM), Multi-View-Stereo (MVS) and Surface Reconstruction from 2017 to 2020.
My research interests and past experiences include multi-view reconstruction (camera calibration, point cloud, mesh, and texture reconstruction from multi-view RGB or Kinect-RGBD), shape parsing (turning rasterized 3D data into parametric CAD shapes), differentiable rendering, and, more broadly, 3D computer vision and graphics.
News
Publications
- Differentiable Convex Polyhedra Optimization from Multi-view ImagesIn European Conference on Computer Vision 2024
- McGrids: Monte Carlo-Driven Adaptive Grids for Iso-Surface Extraction2025
- Dna-rendering: A diverse neural actor repository for high-fidelity human-centric renderingIn Proceedings of the IEEE/CVF International Conference on Computer Vision 2023
- ExtrudeNet: Unsupervised Inverse Sketch and Extrude for Shape ParsingIn European Conference on Computer Vision 2022
- Monocular 3D Object Reconstruction with GAN InversionIn European Conference on Computer Vision 2022
- HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and ModelingIn European Conference on Computer Vision 2022
- Playing for 3D human recoveryarXiv preprint arXiv:2110.07588 2021
- CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape ParsingIn International Conference on Computer Vision 2021
- Messytable: Instance association in multiple camera viewsIn European Conference on Computer Vision 2020