World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
6861
World Ranking
5444
National Ranking
731

Overview

Kai Xu is affiliated with the National University of Defense Technology in China and has an extensive publication record spanning the fields of Engineering and Computer Science. Their work primarily focuses on several key areas including Computer Vision and Pattern Recognition, Computational Mechanics, Aerospace Engineering, Geology, and Artificial Intelligence.

The scientist's research topics cover a range of subjects related to 3D shape modeling and analysis, advanced vision and imaging techniques, 3D surveying and cultural heritage, robotics and sensor-based localization, computer graphics and visualization techniques, advanced neural network applications, and robot manipulation and learning.

Kai Xu has published frequently with several collaborative partners. Notable frequent coauthors include Renjiao Yi, Chenyang Zhu, Hui Huang, Jiazhao Zhang, and Ruizhen Hu. Their body of work appears prominently in venues such as arXiv (Cornell University), SSRN Electronic Journal, ACM Transactions on Graphics, the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), and the Proceedings of the AAAI Conference on Artificial Intelligence.

Recent selected papers exemplify the scope of their research contributions:

  • Geometric Transformer for Fast and Robust Point Cloud Registration, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion, 2021, arXiv (Cornell University)
  • Multicentre, randomized comparison of two-stent and provisional stenting techniques in patients with complex coronary bifurcation lesions: the DEFINITION II trial, 2020, European Heart Journal
  • Efficient One-Pass Multi-View Subspace Clustering with Consensus Anchors, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • RayMVSNet++: Learning Ray-Based 1D Implicit Fields for Accurate Multi-View Stereo, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence

Best Publications

  • GRASS: generative recursive autoencoders for shape structures

    Jun Li;Kai Xu;Siddhartha Chaudhuri;Ersin Yumer

  • GRAINS: Generative Recursive Autoencoders for INdoor Scenes

    Manyi Li;Akshay Gadi Patil;Kai Xu;Siddhartha Chaudhuri

  • MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

    Qian Xie;Yu-Kun Lai;Jing Wu;Zhoutao Wang

  • A novel quantum representation for log-polar images

    Yi Zhang;Kai Lu;Yinghui Gao;Kai Xu

  • Fit and diverse: set evolution for inspiring 3D shape galleries

    Kai Xu;Hao Zhang;Daniel Cohen-Or;Baoquan Chen

  • Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

    Dengsheng Chen;Jun Li;Zheng Wang;Kai Xu

  • GeoTransformer: Fast and Robust Point Cloud Registration With Geometric Transformer

    Unknown

  • PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes

    Rundi Wu;Yixin Zhuang;Kai Xu;Hao Zhang

  • Style-content separation by anisotropic part scales

    Kai Xu;Honghua Li;Hao Zhang;Daniel Cohen-Or

  • Symmetry Hierarchy of Man‐Made Objects

    Yanzhen Wang;Yanzhen Wang;Kai Xu;Kai Xu;Jun Li;Hao Zhang

  • Im2Struct: Recovering 3D Shape Structure from a Single RGB Image

    Chengjie Niu;Jun Li;Kai Xu

  • Data-driven shape analysis and processing

    Kai Xu;Vladimir G. Kim;Qixing Huang;Niloy Mitra

  • Partial intrinsic reflectional symmetry of 3D shapes

    Kai Xu;Hao Zhang;Andrea Tagliasacchi;Ligang Liu

  • Photo-inspired model-driven 3D object modeling

    Kai Xu;Hanlin Zheng;Hao Zhang;Daniel Cohen-Or

  • An efficient and effective convolutional auto-encoder extreme learning machine network for 3d feature learning

    Yueqing Wang;Zhige Xie;Kai Xu;Yong Dou

  • Online 3D Bin Packing with Constrained Deep Reinforcement Learning.

    Hang Zhao;Qijin She;Chenyang Zhu;Yin Yang

  • Local feature point extraction for quantum images

    Yi Zhang;Kai Lu;Kai Xu;Yinghui Gao

  • ASRO-DIO: Active Subspace Random Optimization Based Depth Inertial Odometry

    Unknown

  • 3D shape segmentation and labeling via extreme learning machine

    Zhige Xie;Kai Xu;Ligang Liu;Yueshan Xiong

  • Spatiotemporal CNN for Video Object Segmentation

    Kai Xu;Longyin Wen;Guorong Li;Liefeng Bo

  • Co-hierarchical analysis of shape structures

    Oliver van Kaick;Kai Xu;Hao Zhang;Yanzhen Wang

  • Multi-robot collaborative dense scene reconstruction

    Siyan Dong;Kai Xu;Qiang Zhou;Andrea Tagliasacchi

  • GRASS: Generative Recursive Autoencoders for Shape Structures

    Jun Li;Kai Xu;Siddhartha Chaudhuri;Ersin Yumer

  • Shape2Motion: Joint Analysis of Motion Parts and Attributes From 3D Shapes

    Xiaogang Wang;Bin Zhou;Yahao Shi;Xiaowu Chen

  • Data-Driven Shape Analysis and Processing

    Kai Xu;Vladimir G. Kim;Qixing Huang;Evangelos Kalogerakis

Frequent Co-Authors

Hao Zhang
Hao Zhang Simon Fraser University
Hui Huang
Hui Huang Shenzhen University
Baoquan Chen
Baoquan Chen Peking University
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv University
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Ligang Liu
Ligang Liu University of Science and Technology of China
Ariel Shamir
Ariel Shamir Reichman University
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Qingming Huang
Qingming Huang University of Chinese Academy of Sciences
Longyin Wen
Longyin Wen ByteDance

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