William Seto — accepted AI-conference papers

2021

Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching

Tu-Hoa Pham, William Seto, Shreyansh Daftry, Barry Ridge, Johanna Hansen, Tristan Thrush +8

RA-L 2021

We consider the problem of rover relocalization in the context of the notional Mars Sample Return campaign. In this campaign, a rover (R1) needs to be capable of autonomously navigating and localizing itself within an area of approximately 50 ×50 m using reference images collected years earlier by a

Cited by 11 Source ↗Scholar ↗

2017

Adversarial Inverse Graphics Networks: Learning 2D-To-3D Lifting and Image-To-Image Translation From Unpaired Supervision

Hsiao-Yu Fish Tung, Adam W. Harley, William Seto, Katerina Fragkiadaki

ICCV 2017poster

Researchers have developed excellent feed-forward models that learn to map images to desired outputs, such as to the images' latent factors, or to other images, using supervised learning. Learning such mappings from unlabelled data, or improving upon supervised models by exploiting unlabelled data,…

Cited by 170 PDF ↗Scholar ↗