112 citations · 185 across the 10 of their papers we have counts for
10 papers
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation
Jun Zhou, Kai Chen, Linlin Xu +2
One critical challenge in 6D object pose estimation from a single RGBD image is efficient integration of two different modalities, i.e., color and depth. In this work, we tackle th…
Dynamic Clustering Transformer Network for Point Cloud Segmentation
Dening Lu, Jun Zhou, Kyle Yilin Gao +4
Point cloud segmentation is one of the most important tasks in computer vision with widespread scientific, industrial, and commercial applications. The research thereof has resulte…
NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)
Kyle Gao, Yina Gao, Hongjie He +3
In March 2020, Neural Radiance Field (NeRF) revolutionized Computer Vision, allowing for implicit, neural network-based scene representation and novel view synthesis. NeRF models h…
3DGTN: 3D Dual-Attention GLocal Transformer Network for Point Cloud Classification and Segmentation
Dening Lu, Kyle Gao, Qian Xie +2
Although the application of Transformers in 3D point cloud processing has achieved significant progress and success, it is still challenging for existing 3D Transformer methods to…
Transformers in 3D Point Clouds: A Survey
Dening Lu, Qian Xie, Mingqiang Wei +3
Transformers have been at the heart of the Natural Language Processing (NLP) and Computer Vision (CV) revolutions. The significant success in NLP and CV inspired exploring the use…
3DCTN: 3D Convolution-Transformer Network for Point Cloud Classification
Dening Lu, Qian Xie, Linlin Xu +1
Although accurate and fast point cloud classification is a fundamental task in 3D applications, it is difficult to achieve this purpose due to the irregularity and disorder of poin…
Sentinel-1 Additive Noise Removal from Cross-Polarization Extra-Wide TOPSAR with Dynamic Least-Squares
Peter Q. Lee, Linlin Xu, David A. Clausi
Sentinel-1 is a synthetic aperture radar (SAR) platform with an operational mode called extra wide (EW) that offers large regions of ocean areas to be observed. A major issue with…
The impact of data volume on performance of deep learning based building rooftop extraction using very high spatial resolution aerial images
Hongjie He, Ke Yang, Yuwei Cai +15
Building rooftop data are of importance in several urban applications and in natural disaster management. In contrast to traditional surveying and mapping, by using high spatial re…
DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval
Yun Cao, Yuebin Wang, Junhuan Peng +4
With a small number of labeled samples for training, it can save considerable manpower and material resources, especially when the amount of high spatial resolution remote sensing…
Quantization in Relative Gradient Angle Domain For Building Polygon Estimation
Yuhao Chen, Yifan Wu, Linlin Xu +1
Building footprint extraction in remote sensing data benefits many important applications, such as urban planning and population estimation. Recently, rapid development of Convolut…