Fangchang Ma

Cited by

	All	Since 2018
Citations	1583	1579
h-index	10	10
i10-index	10	10

420

210

105

315

20182019202020212022202349 156 233 359 414 364

Public access

View all

6 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Sertac KaramanProfessor of Aeronautics and Astronautics, Massachusetts Institute of TechnologyVerified email at mit.edu
Ulas AyazJP MorganVerified email at jpmchase.com
Guilherme V. CavalheiroPhD StudentVerified email at mit.edu
Angela DaiTechnical University of MunichVerified email at tum.de
Matthias NießnerProfessor of Computer Science, Technical University of MunichVerified email at tum.de
Qi ShanApple, University of WashingtonVerified email at cs.washington.edu
Vivienne SzeAssociate Professor, EECS at MITVerified email at mit.edu
Tien-Ju YangMassachusetts Institute of TechnologyVerified email at mit.edu
Diana WofkIntel LabsVerified email at intel.com
Alex ColburnUniversity of Washington & AppleVerified email at cs.washington.edu
Luca CarloneAssociate Professor, Massachusetts Institute of TechnologyVerified email at mit.edu
Alexander SchwingUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Xiaoming ZhaoUniversity of Illinois Urbana-ChampaignVerified email at illinois.edu
Justus ThiesProfessor for 3D Graphics & Vision, TU DarmstadtVerified email at tu-darmstadt.de
Yawar SiddiquiPhD Candidate, Visual Computing and AI Chair, Technical University of MunichVerified email at tum.de
David GüeraApple; Purdue UniversityVerified email at apple.com
Ziya ErkoçTechnical University of MunichVerified email at tum.de
Noah StierUniversity of California, Santa BarbaraVerified email at ucsb.edu
Yang Liang3D Computer Vision, AppleVerified email at apple.com
Yajie YanPhD of Computer Science, Washington University in St LouisVerified email at wustl.edu

Fangchang Ma

Apple; MIT

Verified email at apple.com - Homepage

Computer Vision Machine Learning Robotics AR/VR


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Sparse-to-dense: Depth prediction from sparse depth samples and a single image F Ma, S Karaman 2018 IEEE International Conference on Robotics and Automation (ICRA), 1-8, 2018	576	2018
Self-supervised sparse-to-dense: Self-supervised depth completion from lidar and monocular camera F Ma, GV Cavalheiro, S Karaman 2019 International Conference on Robotics and Automation (ICRA), 3288-3295, 2019	435	2019
Fastdepth: Fast monocular depth estimation on embedded systems D Wofk, F Ma, TJ Yang, S Karaman, V Sze 2019 International Conference on Robotics and Automation (ICRA), 6101-6108, 2019	301	2019
Invertibility of convolutional generative networks from partial measurements F Ma, U Ayaz, S Karaman Advances in Neural Information Processing Systems 31, 2018	87	2018
Generative multiplane images: Making a 2d gan 3d-aware X Zhao, F Ma, D Güera, Z Ren, AG Schwing, A Colburn European Conference on Computer Vision, 18-35, 2022	50	2022
Sparse sensing for resource-constrained depth reconstruction F Ma, L Carlone, U Ayaz, S Karaman 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016	36	2016
Retrievalfuse: Neural 3d scene reconstruction with a database Y Siddiqui, J Thies, F Ma, Q Shan, M Nießner, A Dai Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	27	2021
Sparse depth sensing for resource-constrained robots F Ma, L Carlone, U Ayaz, S Karaman The International Journal of Robotics Research 38 (8), 935-980, 2019	27	2019
Texturify: Generating textures on 3d shape surfaces Y Siddiqui, J Thies, F Ma, Q Shan, M Nießner, A Dai European Conference on Computer Vision, 72-88, 2022	20	2022
Hyperdiffusion: Generating implicit neural fields with weight-space diffusion Z Erkoç, F Ma, Q Shan, M Nießner, A Dai arXiv preprint arXiv:2303.17015, 2023	14	2023
On Sensing, Agility, and Computation Requirements for a Data-gathering Agile Robotic Vehicle F Ma, S Karaman arXiv preprint arXiv:1704.02075, 2017	5	2017
Maximum-reward motion in a stochastic environment: The nonequilibrium statistical mechanics perspective F Ma, S Karaman Algorithmic Foundations of Robotics XI: Selected Contributions of the …, 2015	2	2015
FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction N Stier, A Ranjan, A Colburn, Y Yan, L Yang, F Ma, B Angles arXiv preprint arXiv:2304.01480, 2023	1	2023
Algorithms for single-view depth image estimation F Ma Massachusetts Institute of Technology, 2019	1	2019
Supplementary materials-invertibility of convolutional generative networks from partial measurements F Ma, U Ayaz, S Karaman NIPS, 2018	1	2018
StableDreamer: Taming Noisy Score Distillation Sampling for Text-to-3D P Guo, H Hao, A Caccavale, Z Ren, E Zhang, Q Shan, A Sankar, ... arXiv preprint arXiv:2312.02189, 2023		2023
Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today? X Zhao, A Colburn, F Ma, MA Bautista, JM Susskind, AG Schwing arXiv preprint arXiv:2310.08587, 2023		2023
On maximum-reward motion in stochastic environments F Ma Massachusetts Institute of Technology, 2015		2015
Velocity estimator via fusing inertial measurements and multiple feature correspondences from a single camera G Zhou, F Ma, Z Li, T Wang Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on, 2013		2013
HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion-Supplementary Document Z Erkoç, F Ma, Q Shan, M Nießner, A Dai

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors