Binbin photo
BINBIN XU
Staff Researcher
HUAWEI Noah's Ark Lab Canada
Contact Info
My work in Spatial AI aims to develop the perceptual foundations for intelligent agents. I focus on frameworks that fuse real-time sensor measurements with data prior, often through advancements in object-level SLAM, to build a coherent understanding of the world's semantic, geometric, and temporal structure. This enables agents to perform sophisticated reasoning and interact effectively with their physical environment.
Brief Bio
I am currently a staff researcher at HUAWEI Noah's Ark Lab Canada, working on Autonomous Driving and Embodied AI.
I obtained my PhD at Imperial College London (PhD thesis) in 2022, supervised by Prof. Stefan Leutenegger and Prof. Andrew Davison. Follwoing that, I worked as a Postdoc fellow in the Autonomous Space Robotics Lab (ASRL) of University of Toronto with Prof. Tim Barfoot. I received my Master degree in Precision Engineering from the University of Tokyo in 2017, supervised by Prof. Atsushi Yamashita and Prof. Hajime Asama. I got my Bachelor's degree in Information Engineering from South China University of Technology in 2014.
SELECTED PUBLICATIONS
UnPose: Uncertainty-Guided Diffusion Priors for Zero-Shot Pose Estimation
Zhaodong Jiang, Ashish Sinha, Tongtong Cao, Yuan Ren, Bingbing Liu, Binbin Xu
Conference on Robot Learning (CoRL), 2025
project | OpenReview | arXiv
Hippo: Harnessing image-to-3d priors for model-free zero-shot 6d pose estimation
Yibo Liu, Zhaodong Jiang, Binbin Xu, Guile Wu, Yuan Ren, Tongtong Cao, Bingbing Liu, Rui Heng Yang, Amir Rasouli, Jinjun Shan
IEEE Robotics and Automation Letters, 2025 (ICRA 2026 presentation)
project | paper | arXiv
Toward General Object-level Mapping from Sparse Views with 3D Diffusion Priors
Ziwei Liao , Binbin Xu, Steven L. Waslander
Conference on Robot Learning (CoRL), 2024
arXiv | OpenReview / code
Identifying Optimal Launch Sites of High-Altitude Latex-Balloons using Bayesian Optimisation for the Task of Station-Keeping
Jack Saunders, Sajad Saeedi, Adam Hartshorne, Binbin Xu, Özgur Şimşek, Alan Hunter, Wenbin Li
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
project | paper | arXiv | video
NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields
Jens Naumann, Binbin Xu, Stefan Leutenegger, Xingxing Zuo
IEEE Robotics and Automation Letters, 2024
project | paper | arXiv | video | code
FuncGrasp: Learning Object-Centric Neural Grasp Functions from Single Annotated Example Object
Hanzhi Chen, Binbin Xu, Stefan Leutenegger
IEEE International Conference on Robotics and Automation (ICRA), 2024
project | paper | arXiv | video
Incremental Dense Reconstruction from Monocular Video with Guided Sparse Feature Volume Fusion
Xingxing Zuo, Nan Yang, Nathaniel Merrill, Binbin Xu, Stefan Leutenegger
IEEE Robotics and Automation Letters, 2023
paper | arXiv | video
Accurate and Interactive Visual-Inertial Sensor Calibration with Next-Best-View and Next-Best-Trajectory Suggestion
Christopher L Choi, Binbin Xu, Stefan Leutenegger
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
project | paper | arXiv | video | code
What to learn: Features, image transformations, or both?
Yuxuan Chen, Binbin Xu, Frederike Dümbgen, Timothy D Barfoot
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
paper | arXiv | video
Finding Things in the Unknown: Semantic Object-Centric Exploration with an MAV
Sotiris Papatheodorou, Nils Funk, Dimos Tzoumanikas, Christopher Choi, Binbin Xu, Stefan Leutenegger
IEEE International Conference on Robotics and Automation (ICRA), 2023
project | paper | arXiv | video | code
Learning to Complete Object Shapes for Object-level Mapping in Dynamic Scenes
Binbin Xu, Andrew J. Davison, Stefan Leutenegger
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
project | paper | arXiv | video
Visual-Inertial Multi-Instance Dynamic SLAM with Object-level Relocalisation
Yifei Ren*, Binbin Xu*, Christopher L Choi, Stefan Leutenegger
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
project | paper | arXiv | video | code
Deep Probabilistic Feature-metric Tracking
Binbin Xu, Andrew J. Davison, Stefan Leutenegger
IEEE Robotics and Automation Letters (RA-L), Vol. 6, No. 1, pp. 223-230, 2021 (ICRA 2021 presentation)
Honorable Mention of RA-L 2021 Best Paper Award
paper | arXiv | video | code
MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM
Binbin Xu, Wenbin Li, Dimos Tzoumanikas, Michael Bloesch, Andrew Davison, Stefan Leutenegger
IEEE International Conference on Robotics and Automation (ICRA), 2019
paper | arXiv | video | rgb-jacobian | data | code
Spatio-temporal Video Completion in Spherical Image Sequences
Binbin Xu, Sarthak Pathak, Hiromitsu Fujii, Atsushi Yamashita and Hajime Asama
IEEE Robotics and Automation Letters (RA-L), Vol. 2, No. 4, pp. 2032-2039, 2017
paper | video
HONORS
Miscellaneous
  • Having spent wonderful years living in China, Japan, UK, and Canada, I am interested in exploring different cultures and talking with people from different backgrounds. I am fluent in Mandarin, English and Japanese.
  • Associate Editors: ICRA (2024, 2025), IROS (2023, 2024, 2025)
  • Reviewer Service: ICRA, IROS, CoRL, BMVC, TRO, RAL, JFR, TVCG, ...
  • Outside of my research, I love travelling, hiking, climbing, SCUBA diving, and swimming.