2015 -

ANU Computer Science PhD student

Robotic Vision (with emphasis on Deep Learning and combining Vision and Language). Part of the ACRV, supervised by Stephen Gould.
2014 - 2015

Sabre Autonomous Solutions: Engineer

Software for an autonomous grit-blasting robot.
2013 - 2015

FrameFish: Flounder

Virtual try-on software for glasses and sunglasses.
2009 - 2012

University of NSW

Bachelor of Engineering (Computer)
2005 - 2009

Credit Suisse: Equities Analyst

Providing recommendations and research to institutional investors.
2000 - 2004

University of Sydney

Bachelor of Commerce (Finance & Economics)


NEW! (December 2017) We will be presenting our work on Vision-and-Language Navigation at the NIPS 2017 ViGIL workshop.

NEW! (Sept 2017) We have been selected to receive a Facebook ParlAI research award.

NEW! (26 July 2017) We are 1st in the 2017 Visual Question Answering (VQA) Challenge at CVPR! We are also 1st on the MSCOCO image captioning leaderboard. Details and code are on the project page.

NEW! (July 2017) Our paper on out-of-domain image captioning is accepted to EMNLP 2017.

NEW! (April 2017) I am currently interning with the Deep Learning Technology Center working with Lei Zhang and Xiaodong He at Microsoft AI & Research, Redmond, Washington USA.

NEW! (July 2016) We have released a new image caption evaluation metric (SPICE) that improves on CIDEr and METEOR. The paper will appear at ECCV 2016.


Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, Anton van den Hengel

preprint arXiv:1711.07280, 2017.

Project PDF Code

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, Lei Zhang

preprint arXiv:1707.07998, 2017.

Project PDF Code

Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge

Damien Teney, Peter Anderson, Xiaodong He, Anton van den Hengel

preprint arXiv:1708.02711, 2017.

PDF Slides

Guided Open Vocabulary Image Captioning with Constrained Beam Search

Peter Anderson, Basura Fernando, Mark Johnson and Stephen Gould

In Conference on Empirical Methods for Natural Language Processing (EMNLP), 2017.


SPICE: Semantic Propositional Image Caption Evaluation

Peter Anderson, Basura Fernando, Mark Johnson and Stephen Gould

In Proceedings of the European Conference on Computer Vision (ECCV), 2016.

Project PDF Code

Discriminative Hierarchical Rank Pooling for Activity Recognition

Basura Fernando, Peter Anderson, Marcus Hutter and Stephen Gould

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.

PDF Code

An ICP Inspired Inverse Sensor Model with Unknown Data Association

Peter Anderson, Youssef Hunter and Bernhard Hengst

In IEEE International Conference on Robotics and Automation (ICRA), 2013.


Fast Monocular Visual Compass for a Computationally Limited Robot

Peter Anderson and Bernhard Hengst

In Proceedings of the RoboCup International Symposium (RoboCup), 2013.


Robocup Standard Platform League - rUNSWift 2012 Innovations

Sean Harris, Peter Anderson, Belinda Teh, Youssef Hunter, Roger Liu, Bernhard Hengst, Ritwik Roy, Sam Li, Carl Chatfield

In Australasian Conference on Robotics and Automation (ACRA), 2012.


Robot Localisation Using Natural Landmarks

Peter Anderson, Yongki Yusmanthia, Bernhard Hengst and Arcot Sowmya

In Proceedings of the RoboCup International Symposium (RoboCup), 2012.



A Practical Introduction to Deep Learning with Caffe. Presented at the Deep Learning Workshop at AI 2015 / ACRA 2015 in December 2015.

Other Projects


FrameFish is an eyewear virtual try-on system for ecommerce websites. I designed it to load and respond more quickly than competing systems, which can take up to 10 seconds to generate a virtual-try-on image (FrameFish takes about 1 second). FrameFish received an Innovate NSW grant and has been featured on Sky Business News and in the UNSW Young Entrepreneurs series.