Xiaolong Li

lxiaol9@vt.edu.

I am a Senior Applied Research Scientist at Nvidia TAO team. My mission is to build 3D into AI foundations, with current focus on grounding 3D-VLMs into Embodied AI domain. Previously I was an Applied Scientist in Amazon AGI, working on 3D vision problems and diffusion-based video generation. I obtained Ph.D. in computer engineering at Virginia Tech, advised by Prof. A. Lynn Abbott, with research focused on deep 3D representations learning for dynamic scene understanding. I’m interested in AR/VR, Embodied AI, robotics.

During the summer 2019, I am lucky to work with Prof. Shuran Song(now Stanford University), Dr. He Wang(now Peking University), Dr. Li Yi (Google Research, now Tsinghua University), and Johnny Chung Lee(Google Brain Robotics) as a student ML researcher in Google Brain Robotics, Mountain View; in 2020 spring, I did a research internship on 3D perception in MERL, mentored by Prof. Siheng Chen(now Shanghai Jiaotong University), Dr. Alan Sullivan(MERL); in 2021 summer, I worked with Dr. Ishani Chakraborty(Hololens), Dr. Yale Song(MSR), Dr. Bugra Tekin(Hololens) in a research internship. I have also worked with Prof. Yunhui Zhu(VT 3D Optics Group) on X-ray phase imaging.

News

May 16, 2023 Named as Outstanding Reviewer for CVPR 2023
Jun 27, 2022 Joined AWS AI as an applied scientist working on 3D Vision!
Sep 28, 2021 My first submission to NeurIPS 2021 accepted, check paper here!
May 17, 2021 Starting my research internship in Hololens, Microsoft
Sep 21, 2020 Our method ranked 3rd on SemanticKitti Multi-sweep Semantic Segmentation Challenge!
Mar 13, 2020 One paper accepted to CVPR 2020 as Oral presentation!

Education

PhD Student
Aug. 2016-present

Bachelor Degree
Aug. 2012- June 2016



Industry

Applied Scientist
Summer 2022-Present

Research Intern
Summer 2021

Research Intern
Spring 2020

Student Researcher
Summer 2019

Research Intern
Summer 2018



Publications

  1. Li, Xiaolong, Mo, Jiawei, Wang, Ying, Parameshwara, Chethan, Fei, Xiaohan, Swaminathan, Ashwin, Taylor, CJ, Tu, Zhuowen, Favaro, Paolo, and Soatto, Stefano
    Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Model
    arXiv preprint arXiv:2404.18065 2024
  2. Chen, Jiayi, Yan, Mi, Zhang, Jiazhao, Xu, Yinzhen, Li, Xiaolong, Weng, Yijia, Yi, Li, Song, Shuran, and Wang, He
    Tracking and reconstructing hand object interactions from point cloud sequences in the wild
    In Proceedings of the AAAI Conference on Artificial Intelligence 2023
  3. Parameshwara, Chethan, Achille, Alessandro, Trager, Matthew, Li, Xiaolong, Mo, Jiawei, Swaminathan, Ashwin, Taylor, CJ, Venkatraman, Dheera, Fei, Xiaohan, and Soatto, Stefano
    Towards visual foundational models of physical scenes
    arXiv preprint arXiv:2306.03727 2023
  4. Zhao, Yangheng, Wang, Jun, Li, Xiaolong, Hu, Yue, Zhang, Ce, Wang, Yanfeng, and Chen, Siheng
    Number-adaptive prototype learning for 3d point cloud semantic segmentation
    In European Conference on Computer Vision 2022
  5. Wang, Jun, Li, Xiaolong, Sullivan, Alan, Abbott, Lynn, and Chen, Siheng
    Pointmotionnet: Point-wise motion learning for large-scale lidar point clouds sequences
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022
  6. Li, Xiaolong, Weng, Yijia, Yi, Li, Guibas, Leonidas, Abbott, A Lynn, Song, Shuran, and Wang, He
    Leveraging SE (3) Equivariance for Self-Supervised Category-Level Object Pose Estimation
    NeurIPS 2021
  7. Li, Xiaolong, Wang, He, Yi, Li, Guibas, Leonidas J, Abbott, A Lynn, and Song, Shuran
    Category-Level Articulated Object Pose Estimation
    CVPR 2020
    Oral Presentation(5.1%)
  8. Porwal, Prasanna, Pachade, Samiksha, Kokare, Manesh, Deshmukh, Girish .., Li, Xiaolong, and others,
    Idrid: Diabetic retinopathy–segmentation and grading challenge
    Medical image analysis 2020
  9. Wu, Ziling, Li, Xiaolong, and Zhu, Yunhui
    Texture orientation-resolving imaging with structure illumination
    In Computational Imaging II 2017
  10. Chen, Muhao, Gong, Chen, Li, Xiaolong, and Yu, Zongxin
    Research on solving Traveling Salesman Problem based on virtual instrument technology and genetic-annealing algorithms
    In 2015 Chinese Automation Congress (CAC) 2015

SERVICES

I am a reviewer in JEI, TIP, ICCV 2021, ICLR 2022, CVPR 2022, CVPR 2023, ICML 2023, NeurIPS 2023, 3DV 2023, 3DV 2024.