Lingdong Kong


     

     

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

My research pursues to build 3D perception and generation models that are robust, scalable, and generalizable across domains and scenarios, while requiring minimum human annotations.

I have been fortunate to collaborate with NVIDIA Research, OpenMMLab, MMLab@NTU, and ByteDance AI Lab.


🦁 I am open to discussions and collaborations in 3D/4D scene perception, generation, and understanding. Feel free to drop me an email if you find our research backgrounds a potential match.

News

Recent Publications

* equal contributions    ‡ corresponding author


DynamicCity: Large-Scale LiDAR Generation from Dynamic Scenes

Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan, Yu Qiao, Ziwei Liu
arXiv, 2024
PDF   |   Code   |   Home

Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving

Lingdong Kong, Xiang Xu, Jiawei Ren, Wenwei Zhang, Liang Pan, Kai Chen, Wei Tsang Ooi, Ziwei Liu
arXiv, 2024
PDF   |   Code   |   Home

Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding

Lingdong Kong*, Xiang Xu*, Jun Cen, Wenwei Zhang, Liang Pan, Kai Chen, Ziwei Liu
PDF   |   Code   |   Home   |   Poster

Is Your LiDAR Placement Optimized for 3D Scene Understanding?

Ye Li, Lingdong Kong, Hanjiang Hu, Xiaohao Xu, Xiaonan Huang
Spotlight (2.5% = 388/15671)
PDF   |   Code   |   Home   |   Poster

Is Your HD Map Constructor Reliable under Sensor Corruptions?

Xiaoshuai Hao, Mengchuan Wei, Yifan Yang, Haimei Zhao, Hui Zhang, Yi Zhou, Qiang Wang, Weiming Li, Lingdong Kong, Jing Zhang
PDF   |   Code   |   Home   |   Poster

4D Contrastive Superflows Are Dense 3D Representation Learners

Xiang Xu*, Lingdong Kong*, Hui Shuai, Wenwei Zhang, Liang Pan, Kai Chen, Ziwei Liu, Qingshan Liu
PDF   |   Code   |   Home   |   Poster

Learning to Adapt SAM for Segmenting Cross-Domain Point Clouds

Xidong Peng, Runnan Chen, Feng Qiao, Lingdong Kong, Youquan Liu, Tai Wang, Xinge Zhu, Yuexin Ma
PDF   |   Code   |   Poster

OpenESS: Event-Based Semantic Scene Understanding with Open Vocabularies

Lingdong Kong, Youquan Liu, Lai Xing Ng, Benoit R. Cottereau, Wei Tsang Ooi
Highlight (2.8% = 324/11532)
PDF   |   Code   |   Home   |   Poster

Multi-Space Alignments Towards Universal LiDAR Segmentation

Youquan Liu*, Lingdong Kong*, Xiaoyang Wu, Runnan Chen, Xin Li, Liang Pan, Ziwei Liu, Yuexin Ma
PDF   |   Code   |   Home   |   Poster

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

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

Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving

Shaoyuan Xie, Lingdong Kong, Wenwei Zhang, Jiawei Ren, Liang Pan, et al.
PDF   |   Code   |   Home   |   Data

RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions

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

Segment Any Point Cloud Sequences by Distilling Vision Foundation Models

Youquan Liu*, Lingdong Kong*, Jun Cen, Runnan Chen, Wenwei Zhang, et al.
Spotlight (3.0% = 378/12343)
PDF   |   Code   |   Home   |   Demo   |   Poster

Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective

Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, Zhiqiang Xu, et al.
PDF   |   Code   |   Home   |   Demo   |   Poster

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
PDF   |   Code   |   Poster

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
PDF   |   Code   |   Home   |   Data   |   Poster

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
PDF   |   Home   |   Poster

UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase

Youquan Liu, Runnan Chen, Xin Li, Lingdong Kong, Yuchen Yang, et al.
PDF   |   Code   |   Poster

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 Corruptions and Sensor Failure

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

Tech Reports


The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition

Lingdong Kong, Shaoyuan Xie, Hanjiang Hu, Yaru Niu, Wei Tsang Ooi, Benoit R. Cottereau, Lai Xing Ng, Yuexin Ma, Wenwei Zhang, Kai Chen, et al.
Technical Report, 2024
PDF   |   Code   |   Home

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation

Lingdong Kong, Yaru Niu, Shaoyuan Xie, Hanjiang Hu, Lai Xing Ng, et al.
Technical Report, 2023
PDF   |   Code   |   Home

Workshop Organizers

Industrial Experiences

   

NVIDIA Research

Research Intern
Mentor: Dr. Boris Ivanovic
   

OpenMMLab

Research Intern
Mentor: Dr. Wenwei Zhang, Dr. Kai Chen
   

Motional

Autonomous Vehicle Intern
Mentor: Dr. Venice Erin Liong
   

ByteDance AI Lab

Research Scientist Intern
Mentor: Dr. Pengfei Wei

Academic Services

Conference Reviewer

  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE/CVF International Conference on Computer Vision (ICCV)
  • European Conference on Computer Vision (ECCV)
  • Conference on Neural Information Processing Systems (NeurIPS)
  • International Conference on Learning Representations (ICLR)
  • International Conference on Machine Learning (ICML)
  • IEEE International Conference on Robotics and Automation (ICRA)
  • IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Journal Reviewer

  • International Journal of Computer Vision (IJCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Intelligent Vehicles (TIV)
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Robotics and Automation Letters (RA-L)
  • ISPRS Journal of Photogrammetry and Remote Sensing (P&RS)