News

NEW! (December 2018) Organizing the Visually Grounded Interaction and Language Workshop at NIPS.

NEW! (September 2018) Our paper is accepted to NIPS 2018.

NEW! (August 2018) We have one paper accepted to EMNLP 2018.

NEW! (July 2018) Excited to announce that I have started as a research scientist at Georgia Tech, collaborating with Dhruv Batra and Devi Parikh.

NEW! (July 2018) Slides available from our tutorial on Connecting Language and Vision to Actions at ACL 2018.

NEW! (June 2018) Presenting an invited talk at the VQA Challenge and Visual Dialog workshop at CVPR.

NEW! (May 2018) Our Vision and Language Navigation (VLN) challenge and leaderboard is now live on EvalAI!

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Conference Publications

[Google Scholar]

Partially-Supervised Image Captioning

Peter Anderson, Stephen Gould, Mark Johnson

To appear in Advances in Neural Information Processing Systems (NIPS), 2018.

PDF

Disfluency Detection using Auto-Correlational Neural Networks

Paria Jamshid Lou, Peter Anderson, Mark Johnson

In Conference on Empirical Methods for Natural Language Processing (EMNLP), 2018.

PDF

Predicting accuracy on large datasets from smaller pilot data

Mark Johnson, Peter Anderson, Mark Dras, Mark Steedman

In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018. Oral Presentation

PDF

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

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. Spotlight Presentation

Project PDF Code Poster

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

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. Oral Presentation

Project PDF Features Code Captioning Code Poster Slides

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

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

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

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.

PDF

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 Poster Slides

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.

PDF

Fast Monocular Visual Compass for a Computationally Limited Robot

Peter Anderson and Bernhard Hengst

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

PDF

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.

PDF

Robot Localisation Using Natural Landmarks

Peter Anderson, Yongki Yusmanthia, Bernhard Hengst and Arcot Sowmya

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

PDF

Presentations

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

Bio

2018 -

Research Scientist, Georgia Tech

Collaborating with Dhruv Batra and Devi Parikh on research in vision and language, e.g. image captioning, visual question answering (VQA), vision-and-language navigation (VLN), etc.
2015 - 2018

PhD (Computer Science), Australian National University

Machine learning combining visual and linguistic understanding. Affiliated with the ACRV, supervised by Stephen Gould.
2014 - 2015

Engineer, Sabre Autonomous Solutions

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

Flounder, FrameFish

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

BEng (Computer), University of NSW

1st class honours and university medal.
2005 - 2009

Securities Analyst, Credit Suisse

Providing recommendations and research to institutional investors.
2000 - 2004

BComm (Finance & Economics), University of Sydney

1st class honours and university medal.

Other Projects

FrameFish

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.