Megumi Sano — accepted AI-conference papers

2021

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer +18

NeurIPS 2021poster

We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables the simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include real-time near-photo-realistic image ren…

Cited by 342 Source ↗code ↗Scholar ↗

2020

Active World Model Learning with Progress Curiosity

Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber, Daniel Yamins

ICML 2020poster

World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal horizons, and an understanding of…

Cited by 75 Source ↗PDF ↗Scholar ↗