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.

During my PhD, I was part of CVN group of INRIA and CentraleSupélec where I worked under Prof. M. Pawan Kumar and Prof. Nikos Paragios from October 2012 to March 2016.

Research Interests

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.

Amazing PhD Students I closely work with (jointly with Prof. Philip Torr)

I am fortunate to have following amazing external collaborators

Past Students (jointly with Prof. Philip Torr)

Preprints

2) [NEW] Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan*, Kartik Gupta*, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania

1) [NEW] Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania

Publications (Workshops)

3) [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

2) [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

1) 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

Publications (Conferences)

14) [NEW] Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh, Richard Zhang, Puneet K. Dokania, Oliver Wang, Alexei A. Efros, Philip H. S. Torr, Eli Shechtman
In ICCV 2019, Seoul, Korea
Project Page

13) [NEW] Proximal Mean-field for Neural Network Quantization
Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley, Philip H. S. Torr
In ICCV 2019, Seoul, Korea

12) 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
Slides

11) 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

10) 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
Project Page

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.
Project Page

04) Parsimonious Labeling.
Puneet K. Dokania and M. Pawan Kumar
In ICCV 2015, Santiago, Chile.
Report (refer Chapter 3 of my PhD thesis)

03) Learning to Rank using High-Order Information
Puneet K. Dokania , A. Behl, C. V. Jawahar and M. Pawan Kumar
In ECCV 2014, Zurich, Switzerland.
Code

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.
Technical Report

Publications (Journals)

04) [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
Slides

01) Learning-Based Approach for Online Lane Change Intention Prediction
Puneet Kumar, Master Thesis 2012.