photo.jpgQuoc-Huy Tran

CTO at Retrocausal, Inc.
1100 NE Campus Pkwy, 2nd Floor, Seattle, WA 98105

Email: huy [at] retrocausal [dot] ai
Web: http://cs.adelaide.edu.au/~huy

About Me

I am a CTO and Co-Founder at Retrocausal, Inc., a Seattle-based startup building Live Task Guidance for Manufacturing Assembly (Techstars Seattle 2020).

I was a Research Staff Member at NEC Laboratories America, Inc. in San Jose, CA from April 2015 to January 2020, working with Manmohan Chandraker on 3D Scene Understanding with applications in Advanced Driver-Assistance System and Dashcam Video Analysis. Before that, I received my PhD degree in Computer Vision from the University of Adelaide, Australia under the supervision of Tat-Jun Chin and David Suter in December 2014.

LinkedIn - GoogleScholar - ResearchGate

Updates

  • [Apr 2021] Our ICCV 2021 workshop proposal on Computer Vision for the Factory Floor has been accepted.
  • [Apr 2021] One patent is issued by USPTO.
  • [Feb 2021] One paper on temporal video alignment is accepted to CVPR 2021.
  • [Jan 2021] Retrocausal won a SBIR Phase I contract with U.S. Air Force!
  • [Dec 2020] Two patents are issued by USPTO.
  • [Nov 2020] Retrocausal received the Best Demonstration Award at ISMAR 2020!
  • [Nov 2020] One patent is issued by USPTO.
  • [Oct 2020] ThomasNet covers the release of RetroActivity - our human-centric AI solution for quality improvement.
  • [Oct 2020] I gave a talk at Global Young Scholars Vietnam.
  • [Jul 2020] Three papers on visual odometry, monocular depth estimation, and rolling shutter stitching are accepted to ECCV 2020.
  • [Jun 2020] Retrocausal won a SBIR Phase I contract with NASA. Here is the GeekWire article, with cover photo featuring our project!
  • [May 2020] Two patents are issued by USPTO.
  • [Apr 2020] Retrocausal is featured in GeekWire.
  • [Apr 2020] One paper on anomaly detection is accepted to IV 2020.
  • [Feb 2020] Retrocausal is among the 10 startups accepted to Techstars Seattle 2020 Accelerator!
  • [Jan 2020] I resigned from NEC Labs to work on Retrocausal.
  • [Nov 2019] I gave a talk at VinAI Research.
  • [Jun 2019] One paper on learning camera calibration is accepted to IROS 2019.
  • [May 2019] Four patents are issued by USPTO.
  • [Feb 2019] One paper on learning rolling shutter correction is accepted to CVPR 2019 as Oral presentation!

Publications

(Authors with '*' were my interns, and '†' indicates joint first author)

1. *NEW* Learning by Aligning Videos in Time
S. Haresh†, S. Kumar†, H. Coskun, S. N. Syed, A. Konin, M. Z. Zia, Q.-H. Tran
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Link - PDF - Demo
2. *NEW* RetroActivity: Rapidly Deployable Live Task Guidance Experiences [Best Demonstration Award]
A. Konin, S. N. Syed, S. Siddiqui, S. Kumar, Q.-H. Tran, M. Zeeshan Zia
IEEE International Symposium on Mixed and Augmented Reality (ISMAR) Demonstration, 2020
Link - PDF - Demo
3. *NEW* Towards Anomaly Detection in Dashcam Videos
S. Haresh†, S. Kumar†, M. Z. Zia, Q.-H. Tran
IEEE Intelligent Vehicles Symposium (IV), 2020
Link - PDF - Dataset - Talk
4. Image Stitching and Rectification for Hand-Held Cameras
B. Zhuang, Q.-H. Tran
European Conference on Computer Vision (ECCV), 2020
Link - PDF - Supp - Talk
[Project web]
5. Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction
L. Tiwari*, P. Ji, Q.-H. Tran, B. Zhuang, S. Anand, M. Chandraker
European Conference on Computer Vision (ECCV), 2020
Link - PDF - Supp - Talk
[Project web]
6. Learning Monocular Visual Odometry via Self-Supervised Long-Term Modeling
Y. Zou*, P. Ji, Q.-H. Tran, J.-B. Huang, M. Chandraker
European Conference on Computer Vision (ECCV), 2020
Link - PDF - Supp - Talk
[Project web]
7. Degeneracy in Self-Calibration Revisited and a Deep Learning Solution for Uncalibrated SLAM
B. Zhuang*, Q.-H. Tran, G. H. Lee, L. F. Cheong, M. Chandraker
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
Link - PDF - Demo - Slides
[Project web]
8. Learning Structure-And-Motion-Aware Rolling Shutter Correction [Oral Presentation]
B. Zhuang*, Q.-H. Tran, P. Ji, L. F. Cheong, M. Chandraker
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Link - PDF - Supp - Poster - Slides
[Project web]
tpami18.jpg 9a. Deep Supervision with Intermediate Concepts
C. Li*, M. Z. Zia, Q.-H. Tran, X. Yu, G. D. Hager, M. Chandraker
Bay Area Machine Learning Symposium (BayLearn), 2018
Link - PDF - Poster

9b. Deep Supervision with Intermediate Concepts
C. Li*, M. Z. Zia, Q.-H. Tran, X. Yu, G. D. Hager, M. Chandraker
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018
Link - PDF
[Project web]
10. Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences
M. E. Fathy*, Q.-H. Tran, M. Z. Zia, P. Vernaza, M. Chandraker
European Conference on Computer Vision (ECCV), 2018
Link - PDF - Supp - Poster
[Project web]
11. Deep Supervision with Shape Concepts for Occlusion-Aware 3D Object Parsing
C. Li*, M. Z. Zia, Q.-H. Tran, X. Yu, G. D. Hager, M. Chandraker
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Link - PDF - Supp - Poster
Rendered images (Car) - Rendered images (Chair+Sofa) - Annotated CAD models - Annotated KITTI images
[Project web]
12. A Continuous Occlusion Model for Road Scene Understanding
V. Dhiman*, Q.-H. Tran, J. J. Corso, M. Chandraker
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Link - PDF - Supp - Poster
13. Robust Parameter Estimation in Computer Vision: Geometric Fitting and Deformable Registration
Q.-H. Tran
PhD Thesis, Australian Centre for Visual Technologies, University of Adelaide, 2014
Link - PDF
14. As-Projective-As-Possible Image Stitching with Moving DLT
J. Zaragoza, T.-J. Chin, Q.-H. Tran, M. S. Brown, D. Suter
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014
Link - PDF - Supp
Code - Dataset 1 - Dataset 2 - Dataset 3
15. Sampling Minimal Subsets with Large Spans for Robust Estimation
Q.-H. Tran, T.-J. Chin, W. Chojnacki, D. Suter
International Journal of Computer Vision (IJCV), 2013
Link - PDF
16. In Defence of RANSAC for Outlier Rejection in Deformable Registration
Q.-H. Tran, T.-J. Chin, G. Carneiro, M. S. Brown, D. Suter
European Conference on Computer Vision (ECCV), 2012
Link - PDF - Supp
Code

Patents

  1. *NEW* System and Method for Learning Human Activities from Few Demonstrations (US Patent Application)
  2. *NEW* System and Method for Self-Supervised Video Representation Learning (US Patent Application)
  3. *NEW* System and Method for Management and Evaluation of One or More Human Activities (US Patent Application)
  4. System and Method for Building Computational Models of a Goal-Driven Task from Demonstration (US Patent)
  5. Joint Rolling Shutter Image Stitching and Rectification (US Patent Application)
  6. Joint Rolling Shutter Correction and Image Deblurring (US Patent Application)
  7. Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction (US Patent Application)
  8. Self-Supervised Visual Odometry Framework Using Long-Term Modeling and Incremental Learning (US Patent Application)
  9. Image/Video Deblurring Using Convolutional Neural Networks with Applications to SFM/SLAM with Blurred Images/Videos (US Patent Application)
  10. Multi-Task Perception Network with Applications to Scene Understanding and Advanced Driver-Assistance System (US Patent Application)
  11. Camera Self-Calibration Network (US Patent Application)
  12. Rolling Shutter Rectification Using Convolutional Neural Networks with Applications to SFM/SLAM with Rolling Shutter Images/Videos (US Patent Application)
  13. Learning Good Features for Visual Odometry (US Patent)
  14. Aerial Drone Utilizing Pose Estimation (US Patent)
  15. Dense Three-Dimensional Correspondence Estimation with Multi-Level Metric Learning and Hierarchical Matching (US Patent)
  16. Dense Correspondence Estimation with Multi-Level Metric Learning and Hierarchical Matching (US Patent)
  17. Computer Aided Traffic Enforcement Using Dense Correspondence Estimation with Multi-Level Metric Learning and Hierarchical Matching (US Patent)
  18. Landmark Localization on Objects in Images Using Convolutional Neural Networks (US Patent)
  19. Advanced Driver-Assistance System with Landmark Localization on Objects in Images Using Convolutional Neural Networks (US Patent)
  20. Surveillance System with Landmark Localization on Objects in Images Using Convolutional Neural Networks (US Patent)
  21. Action Recognition System with Landmark Localization on Objects in Images Using Convolutional Neural Networks (US Patent)

Activities

  • Conference Reviewers: International Conference on Computer Vision (ICCV), IEEE Conference on Computer Vision and Pattern Recognition (CVPR), European Conference on Computer Vision (ECCV), International Conference on 3D Vision (3DV), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IAPR Conference on Machine Vision Applications (MVA)
  • Workshop Reviewers: Workshop on 3D Reconstruction in the Wild (3DRW) (in conjunction with ECCV/ICCV), Workshop on Visual Odometry and Computer Vision Applications Based on Location Clues (VOCVALC) (in conjunction with CVPR)
  • Journal Reviewers: International Journal of Computer Vision (IJCV), IEEE Transactions on Image Processing (TIP), IEEE Transactions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Journal of Computer Graphics Forum (CGF), Neurocomputing Journal (NEUCOM), The Visual Computer Journal (TVCJ), IEEE Journal of Selected Topics in Signal Processing (STSP), IEEE Signal Processing Letters (SPL)

Awards & Scholarships

  • Best Demonstration Award at IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2020
  • Dean's Commendation for Doctoral Thesis Excellence, 2014
  • International Postgraduate Research Scholarship (IPRS), 2011-2014
  • Australian Postgraduate Award (APA), 2011-2014
  • Scholarship of Pony Chung Foundation - Hyundai Motor Company, 2009
  • Bronze Medal in Vietnam National Olympiad in Informatics (VNOI), 2005
  • Gold Medal in Mekong River Delta Olympiad in Informatics, 2005