Michael Min Sun
PhD student
Princeton CS dept.
msun [at] princeton [dot] edu
Research Interest : Help computer reach human level perception
Applying Machiine Learning on image/video/visual data
Education
09/2007 - present Ph.D in Computer Science at Princeton focuses on Computer vision and Machine Learning
09/2005 - 06/2007 M.S. in Electrical Engineering at Stanford focuses on Machine learning and signal processing
09/1999 - 06/2003 National Chiao Tung University (NCTU), Hsinchu, Taiwan
B.S. in Electrical Engineering, GPA 3.89/4.0, rank 2/47
Project
09/2007 - present , with Prof. Fei Fei Li, Princeton Vision Lab
3D object recognition
06/2006 - 07/2007 Independent Study, with Prof. Andrew Y. Ng, Stanford AI Lab
Real-Scale 3D Reconstruction from Single Monocular Images [result]
01/2006 - 03/2006 RF microelectronics course project, at Stanford
Tri-band (1.8GHz, 2.0GHz, and 2.2GHz) LNA Noise Figure = 0.69dB [report] [slides]
Publication
Learning 3-D Scene Structure from a Single Still Image,
Ashutosh Saxena, Min Sun, Andrew Y. Ng. To appear in IEEE Transactions of Pattern Analysis and Machine Intelligence (PAMI), 2007. [pdf coming soon]Make3D: Depth Perception from a Single Still Image,
Ashutosh Saxena, Min Sun, Andrew Y. Ng. To appear in AAAI, 2008. (Nectar Track) [pdf]Building a 3-D Model From a Single Still Image,
Ashutosh Saxena, Min Sun and Andrew Y. Ng. Demonstration in Neural Information Processing Systems (NIPS), 2007.
Also presented at NIPS Workshop on The Grammar of Vision: Probabilistic Grammar-Based Models for Visual Scene Understanding and Object Categorization, 2007. [png]Learning 3-D Scene Structure from a Single Still Image,
Ashutosh Saxena, Min Sun, Andrew Y. Ng, To appear in ICCV workshop on 3D Representation for Recognition (3dRR-07), 2007.(Best Paper) [ps, pdf]3-D Reconstruction from Sparse Views using Monocular Vision, Ashutosh Saxena, Min Sun, Andrew Y. Ng, To appear in ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), 2007 [ps, pdf]
Useful Link
Machine Learning
Readings for Students (suggested and biased by Eyal Amir)
Optimization
Sedumi http://sedumi.mcmaster.ca/
Computer Vision