activity
20182021
most citedCompositional Scalable Object SLAM

2 citations · 3 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

Self-supervised Geometric Perception

Heng Yang, Wei Dong, Luca Carlone +1

We present self-supervised geometric perception (SGP), the first general framework to learn a feature descriptor for correspondence matching without any ground-truth geometric mode…

cs.RO20202 cited

Compositional Scalable Object SLAM

Akash Sharma, Wei Dong, Michael Kaess

We present a fast, scalable, and accurate Simultaneous Localization and Mapping (SLAM) system that represents indoor scenes as a graph of objects. Leveraging the observation that a…

cs.CV2020

Deep Global Registration

Christopher Choy, Wei Dong, Vladlen Koltun

We present Deep Global Registration, a differentiable framework for pairwise registration of real-world 3D scans. Deep global registration is based on three modules: a 6-dimensiona…

cs.CV2018

Guided Feature Selection for Deep Visual Odometry

Fei Xue, Qiuyuan Wang, Xin Wang +3

We present a novel end-to-end visual odometry architecture with guided feature selection based on deep convolutional recurrent neural networks. Different from current monocular vis…

cs.RO2018

PSDF Fusion: Probabilistic Signed Distance Function for On-the-fly 3D Data Fusion and Scene Reconstruction

Wei Dong, Qiuyuan Wang, Xin Wang +1

We propose a novel 3D spatial representation for data fusion and scene reconstruction. Probabilistic Signed Distance Function (Probabilistic SDF, PSDF) is proposed to depict uncert…

cs.RO2018

An Efficient Volumetric Mesh Representation for Real-time Scene Reconstruction using Spatial Hashing

Wei Dong, Jieqi Shi, Weijie Tang +2

Mesh plays an indispensable role in dense real-time reconstruction essential in robotics. Efforts have been made to maintain flexible data structures for 3D data fusion, yet an eff…