Learning to match 2d images and 3d lidar point clouds for outdoor augmented reality

W Liu, B Lai, C Wang, X Bian, W Yang… - … IEEE Conference on …, 2020 - ieeexplore.ieee.org
Large-scale Light Detection and Ranging (LiDAR) point clouds provide basic 3D information
support for Augmented Reality (AR) in outdoor environments. Especially, matching 2D …

2D3D-MVPNet: Learning cross-domain feature descriptors for 2D-3D matching based on multi-view projections of point clouds

B Lai, W Liu, C Wang, X Fan, Y Lin, X Bian, S Wu… - Applied …, 2022 - Springer
Robust local cross-domain feature descriptors of 2D images and 3D point clouds play an
important role in 2D and 3D vision applications, eg augmented Reality (AR) and robot …

[Retracted] Natural Language Description Generation Method of Intelligent Image Internet of Things Based on Attention Mechanism

J Ouyang, H Yu - Security and Communication Networks, 2022 - Wiley Online Library
With the rapid development of Internet of Things technology, the image data on the Internet
are growing at an amazing speed. How to describe the semantic content of massive image …

Ground camera image and large-scale 3-D image-based point cloud registration based on learning domain invariant feature descriptors

W Liu, B Lai, C Wang, G Cai, Y Su… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Multisource data are captured from different sensors or generated with different generation
mechanisms. Ground camera images (images taken from ground-based camera) and …

Heterogeneous scene matching based on the gradient direction distribution field

Q Li, R Lu, X Yang, S Wang, T Shen, W Xia… - EURASIP Journal on …, 2023 - Springer
Heterogeneous scene matching is a key technology in the field of computer vision. The
image rotation problem is popular and difficult in the field of heterogeneous scene matching …

Heterogeneous scene matching algorithm based on gradient direction distribution field

Q Li, R Lu, X Yang, S Wang, S Tong, W Xia, Z Wei - 2022 - researchsquare.com
Heterogenous scene matching is one of the key technologies in the field of computer vision.
The image rotation problem has been a hot and difficult problem in the field of heterogenous …

Learning Cross-Domain Descriptors for 2D-3D Matching with Hard Triplet Loss and Spatial Transformer Network

B Lai, W Liu, C Wang, X Bian, Y Su, X Lin… - Image and Graphics …, 2021 - Springer
The 2D-3D matching determine the spatial relationship between 2D and 3D space, which
can be used for Augmented Reality (AR) and robot pose estimation, and provides support …

Metric Learning for 2D Image Patch and 3D Point Cloud Volume Matching

B Lai, W Liu, C Wang, S Chen, X Bian… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
Similarity measure of cross-domain descriptors (2D descriptors and 3D descriptors) between
2D image patches and 3D point cloud volumes provides stable retrieval performance and …

3D Point Cloud and BIM Component Retrieval for Subway Stations via Deep Learning.

Y Shi, W Ye, B Qu, H Jia, Z Fu, X Lv, C Wen, W Liu - CECNet, 2022 - ebooks.iospress.nl
It is urgent to digitize the subway equipment to detect the changes in the components in the
subway station in time. In this paper, we use the 3D point cloud of the subway station as a …