 | Sr. Computer Vision Scientist NVIDIA Santa Clara CA 95051 Email: trungp at nvidia.com Phone +1 669 210 9309 Web http://cs.adelaide.edu.au/~trung/ |
About me
This is my new page https://trungtpham.github.io/
I am a Sr. Computer Vision Scientist at NVIDIA, where I am working on visual perception algorithms for driverless cars. Prior to NVIDIA, I was a research fellow at the ARC Centre of Excellence of Robotic Vision. I was working with Prof. Ian Reid on semantic vision for robotic applications. I secured my PhD in Computer Vision in June 2014 from the University of Adelaide, under the supervisions of A. Prof. Tat-Jun Chin and Prof. David Suter. I was awarded a Google PhD Fellowship in 2012. Prior to this, I spent two years (from 2008 to 2010) at Chonnam National University (South Korea) for a Master Degree of Electronic and Computer Engineering.
GoogleScholar Github BitBucket Resume
Research Interests
- Computer vision: SLAM, SfM, 2D/3D scene segmentation, object detection, object tracking, robust geometric fitting.
- Machine learning: Deep learning, Probabilistic graphical models, structured learning.
- Optimization: Stochastic optimization (Monte Carlo Markov Chain methods), discrete combinatorial optimization.
Highlights
- July 2018: 2 papers accepted to ECCV 2018, 1 paper accepted to BMVC 2018.
- June 2018: I am excited to join NVIDIA as a Senior Computer Vision Scientist
- We are organising a Real-World Challenges and New Benchmarks for Deep Learning in Robotic Vision workshop, in conjunction with CVPR 2018.
- 1 paper accepted to Journal: Methods in Ecology and Evolution
- 3 papers accepted to ICRA 2018
- Paper on “Bayesian Data Augmentation for Learning Deep Models” accepted to NIPS 2017.
- I chair the Object Detection, Segementation, and Categorization Session at IROS 2017, Vancouver, September 24–28, 2017.
- Our team (ACRV) won the Amazon Robotic Challenge 2017
- Paper on Object Oriented Semantic Mapping accepted to IROS2017.
- Paper accepted to CVPR2017.
Publications
Stats: PhD Thesis(1), TPAMI(1), TIP(1), CVPR(4), ICCV(1), NIPS(2), IROS(2), ICRA(4).
2018
K. Li, T. Pham, H. Zhan, I. Reid
Efficient Dense Point Cloud Object Reconstruction using Deformation Vector Fields
ECCV 2018
T. Pham, V BG Kumar, T-T Do, G Carneiro, I Reid
Bayesian Instance Segmentation in Open Set World
ECCV 2018
T-T Do, T. Pham, M. Cai, I. Reid
LieNet: Real-time Monocular Object Instance 6D Pose Estimation
BMVC 2018 (Oral)
M Hosseinzadeh, Y Latif, T. Pham, N Suenderhauf, I Reid
Structure Aware SLAM using Quadrics and Planes
RSS-LAIR workshop, 2018
 | JC Hodgson et al. T. Pham et al. Drones count wildlife more accurately and precisely than humans Methods in Ecology and Evolution 2018 PDF |
 | T. T. Pham, TT Do, N. Snderhauf, I. Reid SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes ICRA 2018 PDF |
 | A Milan, T Pham et al. Semantic segmentation from limited training data ICRA 2018 PDF |
 | D. Morrison et al. T. Pham et al. Cartman: The low-cost Cartesian Manipulator that won the Amazon Robotics Challenge ICRA 2018 PDF |
2017
 | T. Tran, T. T. Pham, G. Carneiro, L. Palmer, I. Reid A Bayesian Data Augmentation Approach for Learning Deep Models NIPS 2017 PDF |
 | N. Snderhauf, T. T. Pham, Y. Latif, M. Milford, I. Reid Meaningful Maps - Object-Oriented Semantic Mapping IROS 2017 PDF |
 | Thanh-Toan Do, Dang-Khoa Le Tan, Trung T. Pham, Ngai-Man Cheung Simultaneous Feature Aggregating and Hashing for Large-scale Image Search CVPR 2017 PDF |
 | J Leitner et al The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research ICRA 2017 PDF |
2016
 | T. T. Pham, M. Eich, I. Reid and G. Wyeth Geometrically Consistent Plane Extraction for Dense Indoor 3D Maps Segmentation IROS 2016 PDF Code |
 | T. T. Pham, H. Rezatofighi, T-J Chin, I. Reid Efficient Point Process Inference for Large-scale Object Detection CVPR 2016 PDF |
2015
 | T. T. Pham, I. Reid, S. Gould, Y. Latif Hierarchical Higher-order Regression Forest Fields: An Application to 3D Indoor Scene Labelling ICCV 2015 PDF Regression Tree Fields source code |
 | A. Eriksson, T. T. Pham, T.-J. Chin and I. Reid The k-support norm and convex envelopes of cardinality and rank In Computer Vision and Pattern Recognition (CVPR), 2015. PDF Poster Code |
2014
 | T. T. Pham Robust Parameter Estimation in Computer Vision: Optimisation Methods and Applications PhD thesis, School of Computer Science, The University of Adelaide, April, 2014. |
 | T. T. Pham, T.-J. Chin, K. Schindler and D. Suter, Interacting Geometric Priors for Robust Multi-Model Fitting IEEE Transactions on Image Processing (Accepted July 2014). PDF supplementary Code |
 | T. T. Pham, T.-J. Chin, J. Yu and D. Suter The Random Cluster Model for Robust Geometric Fitting IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), accepted Dec 2013. PDF supplementary Code Video |
2012
 | T. T. Pham, T.-J. Chin, J. Yu and D. Suter The Random Cluster Model for Robust Geometric Fitting In CVPR 2012, Providence, Rhode Island, USA. PDF Video Code |
2011
 | T. T. Pham, T.-J. Chin, J. Yu and D. Suter Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC In NIPS 2011, Granada, Spain. PDF supplementary |
Teaching
- Artificial Intelligent (AI)
- Tutoring: Semester 1 2013.
- Algorithm Design and Data Structure (ADDS),
- Tutoring: Semester 2 2012, Semester 1 2012.
- Practical Supervising: Semester 1 2012.
- Object Oriented Programming (OOP)
- Practical Supervising: Semester 1 2012, Semester 2 2011.
- Introduction Programming (IPe)
- Practical Supervising: Semester 1 2011.