Hi, I have been working as a senior researcher in computer vision and machine learning at the Torr Vision Group (University of Oxford) since 1st March 2019. Prior to that, I was a postdoctoral researcher in the same group from 1st Aug 2016 to 28th Feb 2019. I am also associated with an amazing startup based in Cambridge (U.K.) called FiveAI where we are trying to build driverless cars.
I work in the field of machine learning (optimization, deep learning, generative models etc.) and its applications to vision and language. Please find below few research areas (and related articles) that I am currently excited about.
- Neural Network Discretization: ProxMeanField
- Incremental Learning: RWalk (ECCV18), Tiny Episodic
- Generative Models: MAD-GAN (CVPR18)
- Vision and Language: Flip-Dial (CVPR18), CCA-VD (NIPS-WS18)
- Weakly supervised semantic segmentation: BMVC17, EMMCVPR17
- High-Order Inference: Parsimonious Labeling (ICCV15)
- Structured Prediction: HOAP-SVM (ECCV14), ECCV16, ICML16
Amazing PhD Students I closely work with (jointly with Prof. Philip Torr)
- Arslan Chaudhry (PhD student since Jan 2017)
- Viveka Kulharia (working since September 2017)
- Arnab Ghosh (Intern Jan-July 2017, then joined as a PhD student in TVG)
- Amartya Sanyal (working since August 2018)
- Daniela Massiceti (working since October 2016)
- Jishnu Mukhoti (Internship student since Sept 2018)
I am fortunate to have following amazing external collaborators
Past Students (jointly with Prof. Philip Torr)
- Anuj Sharma (Masters thesis intern, Feb-Aug 2017), [Masters Thesis]
[NEW] Proximal Mean-field for Neural Network Quantization
Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley, Philip H. S. Torr
[NEW] Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania
[NEW] Stable Rank Normalization for Improved Generalization in Neural Networks
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania
In ICML 2019 Workshop, Understanding and Improving Generalization in Deep Learning, Long Beach, USA
[NEW] Continual Learning with Tiny Episodic Memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K. Dokania, Philip H. S. Torr, Marc’Aurelio Ranzato
In ICML 2019 Workshop, MTLRL2019: Workshop on Multi-Task and Lifelong Reinforcement Learning, Long Beach, USA
[NEW] Visual Dialogue without Vision or Dialogue
Daniela Massiceti*, Puneet K. Dokania*, N. Siddharth*, Philip H.S. Torr
In NeurIPS 2018 Workshop, Critiquing and Correcting Trends in Machine Learning, Montréal, Canada
[NEW] Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
Arslan Chaudhry*, Puneet K. Dokania*, Thalaiyasingam Ajanthan*, Philip H. S. Torr
In ECCV 2018, Munich, Germany
[NEW] Multi-Agent Diverse Generative Adversarial Networks
Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri, Philip H. S. Torr, Puneet K. Dokania
In CVPR 2018 (Spotlight), Salt Lake, USA
[NEW] FlipDial: A Generative Model for Two-Way Visual Dialogue
Daniela Massiceti, N. Siddharth, Puneet K. Dokania, Philip H.S. Torr
In CVPR 2018 (Oral), Salt Lake, USA
09) Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation
A. Chaudhry, Puneet K. Dokania, Philip H. S. Torr
In BMVC 2017 (Oral), London, U.K.
08) Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation
Q. Hou, D. Massiceti, Puneet K. Dokania, Y. Wei, M-M. Cheng, Philip H. S. Torr
In EMMCVPR 2017, Venice, Italy.
07) Deformable Registration through Learning of Context-Specific Metric Aggregation
E. Ferrante*, Puneet K. Dokania*, R. Marini, N. Paragios
In MLMI MICCAI 2017, Quebec, Canada.
06) Partial Linearization based Optimization for Multi-class SVM
P. Mohapatra, Puneet K. Dokania, C. V. Jawahar, M. P. Kumar
In ECCV 2016, Amsterdam, the Netherlands.
Supplementary | Poster
05) Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs
A. Osokin, JB Alayrac, I. Lukasewitz, Puneet K. Dokania, S. Lacoste-Julien
In ICML 2016, New York City, USA.
02) Learning-Based Approach for Online Lane Change Intention Prediction
Puneet Kumar , M. Perrollaz, S. Lefevre and C. Laugier
In IEEE Intelligent Vehicle Symposium (IV) 2013, Gold Coast City, Australia.
Video-1 (Best viewed in VLC) | Video-2 (Best viewed in VLC)
01) Discriminative parameter estimation for random walks segmentation
P. Y. Baudin, D. Goodman, Puneet Kumar , N. Azzabou, P. G. Carlier, N. Paragios, M. Pawan Kumar
In MICCAI 2013, Nagoya, Japan.
[NEW] Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration
Enzo Ferrante, Puneet K. Dokania, Rafael M. Silva, N. Paragios
In IEEE Journal of Biomedical and Health Informatics, 2018.
03) Rounding-based Moves for Semi-Metric Labeling
M. Pawan Kumar and Puneet K. Dokania
In JMLR 2016.
02) High Dynamic Range Fuzzy Color Image Enhancement Using Ant Colony System
O. P. Verma, P. Kumar , M. Hanmandlu, S. Chhabra
In Journal of Applied Soft Computing, 2012.
01) A Novel Bacterial Foraging Technique for Edge Detection
O. P. Verma, M. Hanmandlu, P. Kumar , S. Chhabra, A. Jindal
In Pattern Recognition Letters, 2011.
Technical Reports and Thesis
02) High-Order Inference, Ranking, and Regularization Path for Structured SVM
Puneet Kumar Dokania, PhD Thesis 2016
01) Learning-Based Approach for Online Lane Change Intention Prediction
Puneet Kumar, Master Thesis 2012.