Yiming Zhou

Yiming Zhou

3D Vision, VLM/VLA

About

I am currently a Research Scientist at Fraunhofer IZFP and a PhD candidate in the Laboratory of Vision and Digital Systems (LVSN) at Université Laval under the supervision of Prof. Xavier Maldague. I received my Master’s degree from RWTH Aachen University and my Bachelor’s degree in Electrical Engineering from the University of Shanghai for Science and Technology. My research interests include 3D computer vision, vision-language models (VLMs), and vision-language-action (VLA) models.

Entrepreneurship & Tech Transfer

Deep-Tech Spinoff (Co-founder): Passionate about bringing AI from lab to market. Our upcoming spinoff project has successfully secured the prestigious EXIST Research Transfer funding—a flagship grant by the German Federal Ministry for Economic Affairs and Climate Action (BMWK) dedicated to commercializing high-tech research.

Current Work

My current research focuses on Vision-Language-Action (VLA) models for upcoming submissions to ICRA 2027 and IEEE RA-L.

Collaboration

I am always open to research and industry collaborations, particularly in 3D vision, embodied & multimodal AI, and VLM/VLA. Please feel free to contact me via Email or connect with me on LinkedIn.

Selected Publications

  • Efficient Segment Anything with Depth-Aware Fusion and Limited Training Data. Y. Zhou et al., ICASSP, 2026.
  • Dy3DGS-SLAM: Monocular 3D Gaussian Splatting SLAM for Dynamic Environments. Y. Zhou et al., ICRA, 2025.
  • DDN-SLAM: Real-Time Dense Dynamic Neural Implicit SLAM. M. Li, Y. Zhou et al., IEEE Robotics and Automation Letters (RA-L), 2025.

Peer Reviewer for International Journals

Robotics & Autonomous Systems

  • IEEE Robotics and Automation Letters (RA-L)
  • Robotics and Autonomous Systems (Elsevier)

Computer Vision & Multimedia

  • Computer Vision and Image Understanding (CVIU)
  • IEEE Transactions on Multimedia

Artificial Intelligence & Machine Learning

  • Neural Networks
  • Neurocomputing

Measurement & General Engineering

  • Measurement (Journal of the International Measurement Confederation)
  • Alexandria Engineering Journal
  • Results in Engineering (Elsevier)