I am currently a second-year PhD student in Robotics Institute of Carnegie Mellon University, under supervision of Dr. Simon Lucey and Dr. Michael Kaess . I am interested in robot vision, especially for 3D reconstruction and efficient real-world deep network applications. Before CMU, I graduated from Electrical Engineering department of National Taiwan University in 2012, directed by Dr. Li-chen Fu. And worked in Quanta Computer and MediaTek as ISP(Image Signal Processor) algorithm developer for 3 years. Link to CV
Contact: mingfanc at andrew dot cmu dot edu
New argoverse challenges in CVPR2020: link.
How to Cultivate Talent in the Self-Driving Field? Start with Interns. link
- 2018/2019 Summer intern at Argo AI
- Our paper “Deep Component Analysis via Alternating Direction Neural Networks” is accepted by ECCV2018!
Ming-Fang Chang*; John Lambert*; Patsorn Sangkloy*; Jagjeet Singh*; Slawomir Bak; Andrew Hartnett; De Wang; Peter Carr; Simon Lucey; Deva Ramanan; James Hays, “Argoverse: 3D Tracking and Forecasting With Rich Maps”, accepted by CVPR2019 (Thanks to the hard work of all co-authors!!) (Oral) (link) (website)
Calvin Murdock, Ming-Fang Chang, Simon Lucey, Deep Component Analysis via Alternating DirectionNeural Networks, accepted by ECCV2018 (link)
Ming-Fang Chang, Simon Lucey, “Monocular Depth from Small Motion using Surface Normal Prediction”, submitted (link), 2018
Christopher Ham, Ming-Fang Chang, Simon Lucey, and Surya Singh , “Metric Monocular Depth from Small Motion Video Accelerated”, accepted by International Conference on 3D Vision (3DV), 2017 (Spotlight) (link)
- TA for Robot Localization and Mapping(16833), 2019 fall at CMU
- TA for Computer Vision(16720B), 2018 fall at CMU