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 | 84* | 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 | 69 | 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 |
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 | 33 | 2024 |
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 | 27 | 2023 |
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 | 24* | 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 | 24 | 2023 |
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 |
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 | 15 | 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 | 14 | 2024 |
Implicit Concept Removal of Diffusion Models Z Liu*, K Chen*, Y Zhang, J Han, L Hong, H Xu, Z Li, DY Yeung, J Kwok European Conference on Computer Vision (ECCV), 2024 | 12* | 2024 |
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 |
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 European Conference on Computer Vision (ECCV), 2024 | 7 | 2024 |
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 | 5 | 2024 |
Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases K Chen, Y Li, W Zhang, Y Liu, P Li, R Gao, L Hong, M Tian, X Zhao, Z Li, ... arXiv preprint arXiv:2404.10595, 2024 | 4 | 2024 |
Automatic Dense Annotation for Monocular 3D Scene Understanding MA Reza, K Chen, A Naik, DJ Crandall, SH Jung IEEE Access, 2020 | 1 | 2020 |
MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes R Gao, K Chen, Z Li, L Hong, Z Li, Q Xu arXiv preprint arXiv:2405.14475, 2024 | | 2024 |
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 | | |