no code implementations • 21 Apr 2023 • Yu-Shiang Wong, Niloy J. Mitra
A long-standing goal in scene understanding is to obtain interpretable and editable representations that can be directly constructed from a raw monocular RGB-D video, without requiring specialized hardware setup or priors.
no code implementations • CVPR 2021 • Norman Müller, Yu-Shiang Wong, Niloy J. Mitra, Angela Dai, Matthias Nießner
From a sequence of RGB-D frames, we detect objects in each frame and learn to predict their complete object geometry as well as a dense correspondence mapping into a canonical space.
1 code implementation • NAACL 2018 • Chao-Chun Liang, Yu-Shiang Wong, Yi-Chung Lin, Keh-Yih Su
We introduce MeSys, a meaning-based approach, for solving English math word problems (MWPs) via understanding and reasoning in this paper.
no code implementations • 23 Mar 2014 • Yu-Shiang Wong, Hung-Kuo Chu, Niloy J. Mitra
Further, as more scenes are annotated, the system makes better suggestions based on structural and geometric priors learns from the previous annotation sessions.