Lingdong Kong
PhD Student, NUS
I am a second-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 OpenMMLab, ByteDance AI Lab, MMLab@NTU, Motional, and Advanced Digital Sciences Center.
News
- [11/2023] - We are organizing The Second RoboDepth Challenge at ICRA 2024.
- [09/2023] - Seal was selected as a spotlight at NeurIPS 2023.
- [09/2023] - Four papers (RoboDepth, TranSVAE, Seal, and CNS) accepted to NeurIPS 2023.
- [07/2023] - Three papers (Robo3D, RangeFormer, and UniSeg) accepted to ICCV 2023.
- [03/2023] - LaserMix was selected as a highlight at CVPR 2023.
- [02/2023] - Two papers (LaserMix and CLIP2Scene) accepted to CVPR 2023.
- [01/2023] - One paper (ConDA) accepted to ICRA 2023.
- [11/2022] - We are organizing the RoboDepth Challenge at ICRA 2023.
Recent Publications [Complete List]
* indicates equal contributions
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RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions |
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Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective |
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Segment Any Point Cloud Sequences by Distilling Vision Foundation Models |
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Towards Label-Free Scene Understanding by Vision Foundation Models |
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Segment Any RGB-D |
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Robo3D: Towards Robust and Reliable 3D Perception against Corruptions |
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Rethinking Range View Representation for LiDAR Segmentation |
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UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase |
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LaserMix for Semi-Supervised LiDAR Semantic Segmentation |
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CLIP2Scene: Towards Label-Efficient 3D Scene Understanding by CLIP |
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ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation |
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Benchmarking 3D Robustness to Common Corruption and Sensor Failure |
Preprints
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The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
arXiv, 2023
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Benchmarking and Analyzing Bird's Eye View Perception Robustness to Corruptions
arXiv, 2023
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SAM-Guided Unsupervised Domain Adaptation for 3D Segmentation
arXiv, 2023
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Unified 3D and 4D Panoptic Segmentation via Dynamic Shifting Networks
arXiv, 2022
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PointCloud-C: Benchmarking and Analyzing Point Cloud Perception Robustness under Corruptions
arXiv, 2022
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Free Lunch for Co-Saliency Detection: Context Adjustment
arXiv, 2021
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Workshop Organizers
Venue: London, UK
Industrial Experience
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OpenMMLab |
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ByteDance AI Lab |
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Motional |
Academic Services
Conference Reviewer
- IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- IEEE/CVF International Conference on Computer Vision (ICCV)
- 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 Robotics and Automation Letters (RA-L)
- ISPRS Journal of Photogrammetry and Remote Sensing (P&RS)
Teaching Assistant
- CS3263 - Foundations of Artificial Intelligence, AY23/24, Sem 2
- CS4243 - Computer Vision and Pattern Recognition, AY23/24 Sem 1