I am currently a Staff Research Engineer/Scientist at InnoPeak Technology, Inc. (a.k.a OPPO US Research Center) where I am working on R&D for XR (AR/VR/MR) related projects. Previously, I was a Postdoctoral Researcher at the University of Adelaide, where I work with Prof. Ian Reid @ Uni.Adelaide and Dr. Hamid Rezatofighi @ Monash University. I was associated with The Australian Institute for Machine Learning (AIML) @ UniAdelaide and Vision & Learning for Autonomous AI Lab(VL4AI) @ Monash University. My research interests include deep learning and its application in 3D vision and robotic vision.

Piror to that, I received my Ph.D. degree from the University of Adelaide and I was affiliated with the Australian Centre for Robotic Vision, where I was advised by Prof. Ian Reid and Prof. Gustavo Carneiro. Previously, I received my B.Eng degree in Electronic Engineering (first class honors) from The Chinese University of Hong Kong (CUHK), where I was advised by Prof. Xiaogang Wang. Also, I was a visiting researcher in the Unmanned Systems Research Group at The National University of Singapore, where I worked with Prof. Ben M. Chen.

NEWS

• 03/2024: One paper is accepted to CVPR 2024: NARUTO: Neural Active Reconstruction from Uncertain Target Observations. Code will be released soon. Stay tuned!

• 12/2023: We are hiring 2024 research interns (US) and 2024 research interns (China) to work on research projects related to 3D Vision! Feel free to drop me an email if you’re interested.

• 10/2023: One paper is accepted to T-PAMI: SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes

• 02/2023: We are hiring 2023 summer interns to work on research projects related to 3D vision! Feel free to drop me an email if you’re interested.

• 12/2022: It is my pleasure to be recognised as “Outstanding Reviewer” for ACCV 2022 for having provided helpful, high-quality reviews.

• 11/2022: Four new arxiv papers are online:

  SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenes

  ActiveRMAP: Radiance Field for Active Mapping And Planning

  Predicting Topological Maps for Visual Navigation in Unexplored Environments

  What Images are More Memorable to Machines?

• 10/2022: Move to CA, USA and start my new position in InnoPeak Technology, Inc.

• 12/2021: One paper is accepted to 3DV: NVSS: High-quality Novel View Selfie Synthesis

• 12/2021: One paper is accepted to TPAMI: Auto-Rectify Network for Unsupervised Indoor Depth Estimation

• 05/2021: One paper is accepted to IJCV: Unsupervised Scale-consistent Depth Learning from Video

• 03/2021: The extended report for our ICRA2020 (DF-VO) is online: DF-VO: What Should Be Learnt for Visual Odometry?

• 08/2020: Start my Postdoc position in The University of Adelaide.

• 06/2020: One new arxiv paper is online: unsupervised depth learning in indoor

• 01/2020: One paper accepted to ICRA 2020: Visual odometry revisited: What should be learnt?

• 10/2019: One paper accepted to ICCV-Workshop (Deep Learning for Visual SLAM) 2019: Camera relocalization by exploiting multi-view constraints

• 09/2019: One paper accepted to NeurIPS 2019: Scale-consistent depth and ego-motion learning

• 05/2019: Attend ICRA 2019 @ Montreal, Canada

• 01/2019: One paper accepted to ICRA 2019: Self-supervised depth and surface normal learning

• 07/2018: Join HoloLens team @ Microsoft Redmond as a Research Intern

• 07/2018: One paper accepted to ECCV 2018: Efficient dense point cloud object reconstruction

• 06/2018: Attend CVPR 2018 @ Salt Lake City, USA

• 02/2018: One paper accepted to CVPR 2018: Unsupervised monocular depth and visual odometry learning

• 06/2017: One paper accepted to IROS 2017: Deep learning for 2D scan matching and loop closure

• 02/2017: Start my Ph.D in The University of Adelaide