Fenggen Yu(余锋根)
I am an Applied Scientist at Amazon. I obtained my Ph.D. from Gruvi Lab, school of Computing Science at Simon Fraser University, under supervision of Prof. Hao(Richard) Zhang. I received my bachelor degree and master degree from Nanjing University, under supervision of Associate Prof. Yan Zhang. My research interests are on 3D Geometric Modeling and Analysis, Geometric Deep Learning, 3D Content Generation, and 3D Reconstruction from multi-sensors.
We propose LL-Gaussian, a novel framework for 3D reconstruction and enhancement from low-light sRGB images, enabling pseudo normal-light novel view synthesis.
We present a differentiable rendering framework to learn structured 3D abstractions in the form of primitive assemblies from sparse RGB images capturing a 3D object.
We present D2CSG, a neural model composed of two dual and complementary network branches, with dropouts, for unsupervised learning of compact constructive solid geometry (CSG) representations of 3D CAD shapes.