Skip to content
View darrenjkt's full-sized avatar
53 followers · 4 following

Achievements

Achievement: Pull Sharkx3Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Starstruckx2Achievement: Quickdraw

Achievements

Achievement: Pull Sharkx3Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Starstruckx2Achievement: Quickdraw

Block or report darrenjkt

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
darrenjkt/README.md

Hey, I'm Darren 👋

I am a machine learning engineer with a unique blend of research innovation and industry expertise, bringing high-impact, strategic solutions from concept to successful deployment.

Selected Publications 📖

  • (T-IV 2024) MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaption in 3D Object Detection [paper][code]
  • (ICRA 2023) Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object Detection [paper][code]
  • (ITSC 2021) Optimising the selection of samples for robust lidar camera calibration [paper][code]

Pinned Loading

  1. MS3D MS3D Public

    (T-IV, ITSC) Auto-labeling of point cloud sequences for 3D object detection using an ensemble of experts and temporal refinement

    Python 182 20

  2. acfr/cam_lidar_calibration acfr/cam_lidar_calibration Public

    (ITSC 2021) Optimising the selection of samples for robust lidar camera calibration. This package estimates the calibration parameters from camera to lidar frame.

    C++ 500 109

  3. SEE-MTDA SEE-MTDA Public

    (RA-L 2022) See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation.

    Python 51 8

  4. SEE-VCN SEE-VCN Public

    (ICRA 2023) Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object Detection

    Python 22 5