Tianshu Kuai

I am a Master of Science in Applied Computing student in the Department of Computer Science at the University of Toronto, advised by Prof. Igor Gilitschenski. I am also a research intern at Samsung AI Center Toronto.

Previously, I graduated from the Engineering Science program at the University of Toronto, majoring in Robotics. I was fortunate to work with Prof. Steven L. Waslander at TRAILab on 3D LiDAR object detection.

I am interested in the fields of 3D vision, and my current research focuses on 3D scene understanding and manipulation. I also work on real-world image restoration and enhancement. Previously, I worked on self-supervised representation learning for 3D perception in autonomous driving. Aside from vision, I am also interested in robotics research.

I am actively looking for a PhD position for fall 2024.

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clean-usnob MSc in Applied Computing (MScAC), AI Concentration
Department of Computer Science, University of Toronto
Sep 2022 - Mar 2024 | Toronto, ON
clean-usnob B.A.Sc in Engineering Science, Robotics
Faculty of Applied Science and Engineering, University of Toronto
Sep 2017 - Apr 2022 | Toronto, ON

University of Toronto Excellence Award
NSERC Undergraduate Research Award
Dean's Honour List

clean-usnob CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos
Tianshu Kuai, Akash Karthikeyan, Yash Kant, Ashkan Mirzaei, Igor Gilitschenski
CVPR 2023 Workshop
project page / paper / arXiv / code / data

A novel pipeline for building 3D animatable models for articulated and deformable objects from monocular videos without any shape prior or template.

clean-usnob Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss
Anas Mahmoud, Jordan S.K. Hu, Tianshu Kuai, Ali Harakeh, Liam Paull, Steven L. Waslander
CVPR 2023
paper / arXiv

A self-supervised 2D-to-3D representation learning framework for LiDAR semantic segmentation in autonomous driving.

clean-usnob Point Density-Aware Voxels for LiDAR 3D Object Detection
Jordan S.K. Hu, Tianshu Kuai, Steven L. Waslander
CVPR 2022
paper / arXiv / code

An end-to-end two stage LiDAR 3D object detection architecture designed to account for point cloud density variations.

clean-usnob Research Intern
Samsung AI Center Toronto
May 2023 - Current | Toronto, ON

Research on diffusion model based real-world image restoration and enhancement.

clean-usnob 3D Computer Vision Researcher
Toronto Intelligent Systems Lab | Advised by Prof. Igor Gilitschenski
Department of Computer Science, University of Toronto
May 2022 - Current | Toronto, ON

Research on 3D scene representation and manipulation.

clean-usnob Computer Vision Researcher
Toronto Robotics and AI Lab | Advised by Prof. Steven L. Waslander
UTIAS, University of Toronto
May 2021 - April 2023 | Toronto, ON

Research on supervised/self-supervised LiDAR 3D perception models for autonomous vehicles.

clean-usnob Computer Vision Engineer
July 2021 - June 2022 | Toronto, ON

Worked on the real-time 3D Perception system for the University of Toronto's autonomous vehicle team winning the first place in the SAE Autodrive Challenge.

clean-usnob Machine Learning Research Intern
May 2020 - May 2021 | Toronto, ON

Research on deep learning based models for audio signal processing and state-of-the-art methods for neural network compression, and contributed to NPU software compiler pipeline development.

Academic Service
  • Reviewer: CVPR 2023, WACV 2024

  • I am involved in maintaining a curated list of papers in NeRF Editing at awesome-nerf-editing. We welcome contributions to continue expanding and improving this collection.