Skip to content
View Kin-Zhang's full-sized avatar
🎯
Focusing
🎯
Focusing
413 followers · 42 following

Achievements

Achievement: QuickdrawAchievement: Starstruckx2Achievement: Pull Sharkx2

Achievements

Achievement: QuickdrawAchievement: Starstruckx2Achievement: Pull Sharkx2

Highlights

  • Pro

Organizations

@KTH-RPL @HKUSTGZ-IADC

Block or report Kin-Zhang

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
Kin-Zhang/README.md

Hi there 👋 , welcome to Kin's GitHub page!

  • 🌱 I'm a Ph.D. student at the DIVISION OF ROBOTICS, PERCEPTION AND LEARNING at KTH Royal Institute of Technology, supervised by Prof. Patric Jensfelt and Prof. Olov Andersson. My research mainly focuses on dynamic awareness in point clouds based on our WASP project. Still exploring...
  • ✨ MPhil Graduated in Aug 2022. I was a MPhil Student at the Robotics Institute RAMLAB of The Hong Kong University of Science and Technology, supervised by Prof. Ming Liu and Prof. Wei Zhang. My MPhil research mainly focused on planning and end-to-end learning for self-driving.
  • 😄 I enjoy learning about different things and techniques, diving into theory, and blogging.
  • ⚡ Life ideal: open-source amazing project, travel around the world

(｡･∀･)ﾉﾞ嗨 👋 , 這裡是張聰明

  • 🌱 現在我是瑞典皇家理工學院的在讀博士，師從Prof. Patric Jensfelt和Prof. Olov Andersson，研究方向：点云中的动态物体感知等工作，還在探索中...
  • ✨ 2022年8月畢業：在劉明教授和張薇教授指導下，於香港科技大學機器人研究所RI RAMLAB 攻讀研究型碩士。碩士期間主要研究無人駕駛中的運動規劃和端到端學習下的自動駕駛系統設計
  • 😄 享受學習不同的知識和技巧，喜歡探究理論部分，同時喜歡寫博客
  • ⚡ 人生理想：想一些有意思idea，然後開源 耶✌️，環遊世界

Pinned Loading

  1. KTH-RPL/DynamicMap_Benchmark KTH-RPL/DynamicMap_Benchmark Public

    The First Dynamic Map Removal Benchmark | Included 8 SOTA methods | Continous updating

    Jupyter Notebook 300 20

  2. KTH-RPL/DeFlow KTH-RPL/DeFlow Public

    [ICRA'24] DeFlow: Decoder of Scene Flow Network in Autonomous Driving

    Python 103 6

  3. KTH-RPL/dufomap KTH-RPL/dufomap Public

    [RA-L'24] DUFOMap: Efficient Dynamic Awareness Mapping

    C++ 166 17

  4. KTH-RPL/SeFlow KTH-RPL/SeFlow Public

    [ECCV'24] SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving

    Python 71 3

  5. mmfn mmfn Public

    [IROS'22] MMFN: Multi-Modal Fusion Net for End-to-End Autonomous Driving

    Python 96 9

  6. carla-expert carla-expert Public

    All kind of experts that can collect data for e2e learning in CARLA; 根据现有的开源代码，收集的相关experts

    Python 118 3