I obtained my PhD from the 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. This page might be outdated due to my graduation.

Contact: mf.allie.chang at gmail dot com

Recent Publications

Google Scholar

1. Ming-Fang Chang, Akash Sharma, Michael Kaess, and Simon Lucey, “Neural Radiance Fields with LiDAR Maps”, ICCV 2023 (code paper).

2. Ming-Fang Chang, Ratnesh Kumar, De Wang, and James Hays, “Systems and methods for producing amodal cuboids”, US patent application (link)

3. Ming-Fang Chang, Yipu Zhao, Rajvi Shah, Jakob J. Engel, Michael Kaess, and Simon Lucey, “Long-term Visual Map Sparsification with Heterogeneous GNN”, CVPR2022 (link)

4. Ming-Fang Chang, Wei Dong, Joshua Mangelson, Michael Kaess, and Simon Lucey, “Map Compressibility Assessment for LiDAR Registration”, IROS2021 (link)

5. Ming-Fang Chang, Joshua Mangelson, Michael Kaess, and Simon Lucey, “HyperMap: Compressed 3D Map for Monocular Camera Registration”, ICRA2021 (link)

6. 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”, CVPR2019 Oral (Thanks to the hard work of all co-authors!!) (link) (website)

7. Calvin Murdock, Ming-Fang Chang, Simon Lucey, Deep Component Analysis via Alternating DirectionNeural Networks, ECCV2018 (link)

8. Christopher Ham, Ming-Fang Chang, Simon Lucey, and Surya Singh , “Metric Monocular Depth from Small Motion Video Accelerated”, 3DV2017 (Spotlight) (link)

Other News

• I attended the Doctoral Consortium in CVPR 2023 (acceptance rate 13%).

• I now serve as reviewers for ICCV, CVPR, ICRA, IROS, and RA-L.

• 2021 Summer intern at Meta Reality Labs Research

• Argoverse challenges in CVPR2020: link. [Tracking challenge] [Forecasting challenge]

• How to Cultivate Talent in the Self-Driving Field? Start with Interns. link

• News about Argoverse: Forbes/ Our blog post/ CNET/ TechCrunch/ FordAuthority

• 2018/2019 Summer intern at Argo AI

Teaching

1. TA for Robot Localization and Mapping(16833), 2019 fall at CMU
2. TA for Computer Vision(16720B), 2018 fall at CMU