Hi, I’m a senior researcher in machine learning and computer vision at the Torr Vision Group (University of Oxford) and a principal researcher at an amazing startup based in Cambridge (U.K.) called Five AI 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 (officially – implies PhD students I formally co-supervise at Oxford with Phil, write regular reviews/reports for them etc.)

Past Students I worked with

  • Arslan Chaudhry (PhD student (official), Jan 2017 to Nov 2020. joined DeepMind), [PhD Thesis]
  • Arnab Ghosh (Intern Jan-July 2017, then joined as a PhD student in TVG and collaborated until the mid of 2019)
  • Daniela Massiceti (from October 2016 until Dec 2018. Moved to MSR Cambridge)
  • Anuj Sharma (Masters thesis intern (official), Feb-Aug 2017, moved to Five AI), [Masters Thesis]

Preprints

01) Robustness via Deep Low-Rank Representations
Amartya Sanyal, Varun Kanade, Philip H. S. Torr, Puneet K. Dokania
Project Page

Publications (Conferences)

22) [NEW] Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan*, Kartik Gupta*, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
In AISTATS 2021

21) [NEW] Progressive Skeletonization: Trimming more fat from a network at initialization
Pau de Jorge, Amartya Sanyal, Harkirat S. Behl, Gregory Rogez, Puneet K. Dokania
In ICLR 2021

20) [NEW] How benign is benign overfitting?
Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr
In ICLR 2021 Spotlight

19) [NEW] No Cost Likelihood Manipulation at Test Time For Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania , Vineet Gandhi
In ICLR 2021

18) [NEW] Using Hindsight to Anchor Past Knowledge in Continual Learning
Arslan Chaudhry, Albert Gordo, Puneet K. Dokania , Philip Torr, David Lopez-Paz
In AAAI 2021

17) Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti*, Viveka Kulharia*, Amartya Sanyal, Stuart Golodetz, Philip H.S. Torr, Puneet K. Dokania
In NeurIPS 2020

16) Continual Learning in Low-rank Orthogonal Subspaces
Arslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H.S. Torr
In NeurIPS 2020

15) GDumb: A Simple Approach that Questions Our Progress in Continual Learning
Ameya Prabhi, Philip H. S. Torr, Puneet K. Dokania
In ECCV 2020 (Oral)

14) Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania
In ICLR 2020 (Spotlight), Addis Ababa Ethiopia

13) 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

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

11) 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

10) 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

09) 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

08) 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.

07) 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.

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 (Workshops)

08) [NEW] On Batch Normalisation for Approximate Bayesian Inference
Jishnu Mukhoti, Puneet K. Dokania, Philip H.S. Torr, Yarin Gal
In 3rd Symposium on Advances in Approximate Bayesian Inference 2020

07) [NEW] Choice of Representation Matter for Adversarial Robustness
Amartya Sanyal, Varun Kanade, Puneet K. Dokania, Philip H.S. Torr
In NeurIPS 2020 Workshop, Interpretable Inductive Biases and Physically Structured Learning

06) [NEW] Interpolation Noisy Datasets hurt Adversarial Robustness
Amartya Sanyal, Varun Kanade, Puneet K. Dokania, Philip H.S. Torr
In NeurIPS 2020 Workshop, Dataset Curation and Security

05) [NEW] On using Focal Loss for Neural Network Calibration
Jishnu Mukhoti*, Viveka Kulharia*, Amartya Sanyal, Stuart Golodetz, Philip H.S. Torr, Puneet K. Dokania
In ICML 2020 Workshop (Spotlight), Uncertainty and Robustness in Deep Learning

04) 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

03) 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

02) 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

01) Deformable Registration through Learning of Context-Specific Metric Aggregation
E. Ferrante*, Puneet K. Dokania*, R. Marini, N. Paragios
In MLMI MICCAI 2017, Quebec, Canada.

Publications (Journals)

04) 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.