no code implementations • 10 Mar 2022 • Nathan Powell, Bowei Liu, Jia Guo, Sai Tej Parachuri, Andrew J. Kurdila
It is assumed that motions are supported on a low-dimensional, unknown configuration manifold $Q$ that is regularly embedded in high dimensional Euclidean space $X:=\mathbb{R}^d$.
3 code implementations • 9 Jun 2021 • Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
It also outperforms state-of-the-art methods on ScanObjectNN, a real-world point cloud benchmark, and demonstrates better cross-dataset generalization.
Ranked #18 on Point Cloud Classification on PointCloud-C
2 code implementations • 1 Jan 2021 • Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
It also outperforms state-of-the-art methods on ScanObjectNN, a real-world point cloud benchmark, and demonstrates better cross-dataset generalization.
Ranked #11 on 3D Point Cloud Classification on ModelNet40-C
no code implementations • 1 Oct 2018 • Martin Loncaric, Bowei Liu, Ryan Weber
We present a powerful new loss function and training scheme for learning binary hash codes with any differentiable model and similarity function.
no code implementations • 9 Feb 2018 • Martin Loncaric, Bowei Liu, Ryan Weber
We present a powerful new loss function and training scheme for learning binary hash functions.