| SODA10M: a large-scale 2D self/semi-supervised object detection dataset for autonomous driving J Han, X Liang, H Xu, K Chen, L Hong, J Mao, C Ye, W Zhang, Z Li, ... Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2021 | 74* | 2021 |
| CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving K Li*, K Chen*, H Wang*, L Hong, C Ye, J Han, Y Chen, W Zhang, C Xu, ... European Conference on Computer Vision (ECCV), 2022 | 61 | 2022 |
| Multisiam: Self-supervised multi-instance siamese representation learning for autonomous driving K Chen, L Hong, H Xu, Z Li, DY Yeung International Conference on Computer Vision (ICCV), 2021 | 53 | 2021 |
| Mixed Autoencoder for Self-supervised Visual Representation Learning K Chen, Z Liu, L Hong, H Xu, Z Li, DY Yeung Computer Vision and Pattern Recognition (CVPR), 2023 | 25 | 2023 |
| MagicDrive: Street View Generation with Diverse 3D Geometry Control R Gao*, K Chen*, E Xie, L Hong, Z Li, DY Yeung, Q Xu International Conference on Learning Representations (ICLR), 2024 | 22 | 2024 |
| Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing Z Liu, J Han, K Chen, L Hong, H Xu, C Xu, Z Li AAAI Conference on Artificial Intelligence (AAAI), 2022 | 21* | 2022 |
| GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation K Chen, E Xie, Z Chen, Y Wang, L Hong, Z Li, DY Yeung International Conference on Learning Representations (ICLR), 2024 | 18* | 2024 |
| Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning Y Gou*, Z Liu*, K Chen*, L Hong, H Xu, A Li, DY Yeung, JT Kwok, ... arXiv preprint arXiv:2312.12379, 2023 | 17 | 2023 |
| Gaining wisdom from setbacks: Aligning large language models via mistake analysis K Chen, C Wang, K Yang, J Han, L Hong, F Mi, H Xu, Z Liu, W Huang, Z Li, ... International Conference on Learning Representations (ICLR), 2024 | 16 | 2024 |
| Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts Z LIU*, K Chen*, J Han, L HONG, H Xu, Z Li, J Kwok International Conference on Learning Representations (ICLR) (spotlight), 2023 | 16 | 2023 |
| Geom-Erasing: Geometry-Driven Removal of Implicit Concept in Diffusion Models Z Liu*, K Chen*, Y Zhang, J Han, L Hong, H Xu, Z Li, DY Yeung, J Kwok arXiv preprint arXiv:2310.05873, 2023 | 10 | 2023 |
| TrackDiffusion: Tracklet-Conditioned Video Generation via Diffusion Models P Li*, K Chen*, Z Liu*, R Gao, L Hong, G Zhou, H Yao, DY Yeung, ... arXiv preprint arXiv:2312.00651, 2023 | 8* | 2023 |
| Automatic annotation for semantic segmentation in indoor scenes MA Reza, AU Naik, K Chen, DJ Crandall International Conference on Intelligent Robots and Systems (IROS), 2019 | 8 | 2019 |
| DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception Y Wang*, R Gao*, K Chen*, K Zhou, Y Cai, L Hong, Z Li, L Jiang, ... Computer Vision and Pattern Recognition (CVPR), 2024 | 4 | 2024 |
| Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation Y Gou*, K Chen*, Z Liu*, L Hong, H Xu, Z Li, DY Yeung, JT Kwok, Y Zhang arXiv preprint arXiv:2403.09572, 2024 | 3 | 2024 |
| Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases Y Li*, W Zhang*, K Chen*, Y Liu, P Li, R Gao, L Hong, M Tian, X Zhao, Z Li, ... arXiv preprint arXiv:2404.10595, 2024 | 1 | 2024 |
| Automatic Dense Annotation for Monocular 3D Scene Understanding MA Reza, K Chen, A Naik, DJ Crandall, SH Jung IEEE Access, 2020 | 1 | 2020 |
| Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment Z Liu*, Y Gou*, K Chen*, L Hong, J Gao, F Mi, Y Zhang, Z Li, X Jiang, ... arXiv preprint arXiv:2405.00557, 2024 | | 2024 |
| Supplementary Materials of “MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving” K Chen, L Hong, H Xu, Z Li, DY Yeung | | |
Lanqing HONGNational University of Singapore, Huawei Noah's Ark LabVerified email at u.nus.edu
