1Nanyang Technological University of Singapore, 2Singapore University of Technology and Design, 3Institute of Infocomm Research
We introduced SPACE: A Simulator for Physical Interactions and Causal Learning in
3D Environments. The SPACE simulator allows us to generate the SPACE dataset, a synthetic video dataset in a 3D
environment, to systematically evaluate physics-based models on a range of physical causal reasoning tasks. Inspired by
daily object interactions, the SPACE dataset comprises videos
depicting three types of physical events: containment, stability and contact. These events make up the vast majority
of the basic physical interactions between objects. We then
further evaluate it with a state-of-the-art physics-based deep
model and show that the SPACE dataset improves the learning of intuitive physics with an approach inspired by curriculum learning.
@inproceedings{duan2021space, title={SPACE: A Simulator for Physical Interactions and Causal Learning in 3D Environments}, author={Duan, Jiafei and Yu, Samson and Tan, Cheston},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision}, pages={2058--2063}, year={2021} }
