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20172023
most citedRPM-Net: Robust Point Matching using Learned Features

624 citations · 1.4k across the 39 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.RO2018

Object Detection and Motion Planning for Automated Welding of Tubular Joints

Syeda Mariam Ahmed, Yan Zhi Tan, Gim Hee Lee +2

Automatic welding of tubular TKY joints is an important and challenging task for the marine and offshore industry. In this paper, a framework for tubular joint detection and motion…

cs.RO2018★ 12 cited

Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System

Lionel Heng, Benjamin Choi, Zhaopeng Cui +10

Project AutoVision aims to develop localization and 3D scene perception capabilities for a self-driving vehicle. Such capabilities will enable autonomous navigation in urban and ru…

cs.CV2018★ 417 cited

3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

Zi Jian Yew, Gim Hee Lee

In this paper, we propose the 3DFeat-Net which learns both 3D feature detector and descriptor for point cloud matching using weak supervision. Unlike many existing works, we do not…

cs.CV2018★ 1 cited

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition

Mikaela Angelina Uy, Gim Hee Lee

Unlike its image based counterpart, point cloud based retrieval for place recognition has remained as an unexplored and unsolved problem. This is largely due to the difficulty in e…

cs.CV2018★ 30 cited

Convolutional Sequence to Sequence Model for Human Dynamics

Chen Li, Zhen Zhang, Wee Sun Lee +1

Human motion modeling is a classic problem in computer vision and graphics. Challenges in modeling human motion include high dimensional prediction as well as extremely complicated…

cs.CV2018★ 96 cited

SO-Net: Self-Organizing Network for Point Cloud Analysis

Jiaxin Li, Ben M. Chen, Gim Hee Lee

This paper presents SO-Net, a permutation invariant architecture for deep learning with orderless point clouds. The SO-Net models the spatial distribution of point cloud by buildin…