Lingdong Kong

  PhD Student, NUS



I am a first-year Ph.D. student in the Department of Computer Science at the National University of Singapore, under Prof. Wei Tsang Ooi. I am also closely with Dr. Benoit Cottereau from CNRS, Dr. Lai Xing Ng from A*STAR, and Prof. Ziwei Liu from S-Lab, Nanyang Technological University, Singapore.

I work in the fields of deep learning and computer vision, with particular focuses on 3D perception, domain adaptation, and visual representation learning.

My research pursues to build robust and scalable perception models that can be generalized across different domains and scenarios, with minimum or no human annotations needed.

I am fortunate to have research attachments and internships at Shanghai AI Lab, ByteDance AI Lab, MMLab@NTU, Motional, and Advanced Digital Sciences Center.


Recent Publication [Full List]

* indicates equal contribution

LaserMix for Semi-Supervised LiDAR Semantic Segmentation

Lingdong Kong*, Jiawei Ren*, Liang Pan, Ziwei Liu
Highlight (2.5% = 235/9155)
PDF   |   Code   |   Home   |   Video   |   Poster

CLIP2Scene: Towards Label-Efficient 3D Scene Understanding by CLIP

Runnan Chen, Youquan Liu, Lingdong Kong, Xinge Zhu, Yuexin Ma, Yikang Li, Yuenan Hou, Yu Qiao, Wenping Wang
PDF   |   Code   |   Video   |   Poster

ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation

Lingdong Kong, Niamul Quader, Venice Erin Liong
PDF   |   Code   |   Home   |   Data   |   Poster

Benchmarking 3D Robustness to Common Corruption and Sensor Failure

Lingdong Kong*, Youquan Liu*, Xin Li*, Runnan Chen, Wenwei Zhang, et al.
Best Workshop Paper Award
PDF   |   Code   |   Home   |   Data

Benchmarking Out-of-Distribution Depth Estimation under Corruptions

Lingdong Kong, Shaoyuan Xie, Hanjiang Hu, Benoit Cottereau, Lai Xing Ng, Wei Tsang Ooi
PDF   |   Code   |   Home   |   Data


Rethinking Range View Representation for LiDAR Segmentation

Lingdong Kong, Youquan Liu, Runnan Chen, Yuexin Ma, Xinge Zhu, Yikang Li, Yuenan Hou, Yu Qiao, Ziwei Liu
arXiv, 2023
PDF   |   Home

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

Lingdong Kong*, Youquan Liu*, Xin Li*, Runnan Chen, Wenwei Zhang, Jiawei Ren, Liang Pan, Kai Chen, Ziwei Liu
arXiv, 2023
PDF   |   Code   |   Home   |   Data

Towards Label-Free Scene Understanding by Vision Foundation Models

Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge Zhu, Yuexin Ma, Tongliang Liu, Wenping Wang
arXiv, 2023
PDF   |   Code

Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective

Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, et al.
arXiv, 2022
PDF   |   Code   |   Home   |   Demo

Unified 3D and 4D Panoptic Segmentation via Dynamic Shifting Network

Fangzhou Hong, Lingdong Kong, Hui Zhou, Xingge Zhu, Hongsheng Li, Ziwei Liu
arXiv, 2022
PDF   |   Code

PointCloud-C: Benchmarking and Analyzing Point Cloud Perception Robustness under Corruptions

Jiawei Ren*, Lingdong Kong*, Liang Pan, Ziwei Liu
arXiv, 2022
PDF   |   Code   |   Home   |   Data

Free Lunch for Co-Saliency Detection: Context Adjustment

Lingdong Kong, Prakhar Ganesh, Junhao Liu, Le Zhang, Yao Chen
arXiv, 2021
PDF   |   Home

Workshop Organizer

Talk & Presentation

Industrial Experience


ByteDance AI Lab

Research Scientist Intern
Advisor: Dr. Pengfei Wei


Autonomous Vehicle Intern
Advisor: Dr. Venice Erin Liong

Academic Service

Conference Reviewer

  • IEEE/CVF International Conference on Computer Vision (ICCV)
  • Neural Information Processing Systems (NeurIPS)
  • International Conference on Learning Representations (ICLR)
  • International Conference on Machine Learning (ICML)
  • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)
  • IEEE Transactions on Neural Networks and Learning Systems (T-NNLS)
  • IEEE Transactions on Intelligent Vehicles (T-IV)
  • IEEE Robotics and Automation Letters (RA-L)