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2020 – today
- 2023
[i28]Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Liwei Wang:
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. CoRR abs/2303.11052 (2023)- 2022
- [c20]Zhili Liu, Jianhua Han, Lanqing Hong, Hang Xu, Kai Chen, Chunjing Xu, Zhenguo Li:
Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing. AAAI 2022: 1854-1862 - [c19]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. AAAI 2022: 8945-8953 - [c18]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
Re-examining Distillation for Continual Object Detection. BMVC 2022: 807 - [c17]Longhui Yu, Yifan Zhang, Lanqing Hong, Fei Chen, Zhenguo Li:
Dual-Curriculum Teacher for Domain-Inconsistent Object Detection in Autonomous Driving. BMVC 2022: 872 - [c16]Nanyang Ye, Kaican Li, Haoyue Bai, Runpeng Yu, Lanqing Hong, Fengwei Zhou, Zhenguo Li, Jun Zhu:
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization. CVPR 2022: 7937-7948 - [c15]Shipeng Yan, Lanqing Hong, Hang Xu, Jianhua Han, Tinne Tuytelaars, Zhenguo Li, Xuming He:
Generative Negative Text Replay for Continual Vision-Language Pretraining. ECCV (36) 2022: 22-38 - [c14]Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, Zhenguo Li:
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction. ECCV (39) 2022: 125-142 - [c13]Kaican Li, Kai Chen, Haoyu Wang, Lanqing Hong, Chaoqiang Ye, Jianhua Han, Yukuai Chen, Wei Zhang, Chunjing Xu, Dit-Yan Yeung, Xiaodan Liang, Zhenguo Li, Hang Xu:
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving. ECCV (38) 2022: 406-423 - [c12]Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng:
Generalizing Few-Shot NAS with Gradient Matching. ICLR 2022 - [c11]Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng:
How Well Does Self-Supervised Pre-Training Perform with Streaming Data? ICLR 2022 - [c10]Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu:
Memory Replay with Data Compression for Continual Learning. ICLR 2022 - [i27]Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu:
Memory Replay with Data Compression for Continual Learning. CoRR abs/2202.06592 (2022) - [i26]Kaican Li, Kai Chen, Haoyu Wang, Lanqing Hong, Chaoqiang Ye, Jianhua Han, Yukuai Chen, Wei Zhang, Chunjing Xu, Dit-Yan Yeung, Xiaodan Liang, Zhenguo Li, Hang Xu:
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving. CoRR abs/2203.07724 (2022) - [i25]Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng:
Generalizing Few-Shot NAS with Gradient Matching. CoRR abs/2203.15207 (2022) - [i24]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
Re-examining Distillation For Continual Object Detection. CoRR abs/2204.01407 (2022) - [i23]Zhili Liu, Jianhua Han, Lanqing Hong, Hang Xu, Kai Chen, Chunjing Xu, Zhenguo Li:
Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing. CoRR abs/2205.13267 (2022) - [i22]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. CoRR abs/2206.05749 (2022) - [i21]Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, Zhenguo Li:
DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction. CoRR abs/2209.06351 (2022) - [i20]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
CLAD: A realistic Continual Learning benchmark for Autonomous Driving. CoRR abs/2210.03482 (2022) - [i19]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. CoRR abs/2210.05398 (2022) - [i18]Longhui Yu, Yifan Zhang, Lanqing Hong, Fei Chen, Zhenguo Li:
Dual-Curriculum Teacher for Domain-Inconsistent Object Detection in Autonomous Driving. CoRR abs/2210.08748 (2022) - [i17]Shipeng Yan, Lanqing Hong, Hang Xu, Jianhua Han, Tinne Tuytelaars, Zhenguo Li, Xuming He:
Generative Negative Text Replay for Continual Vision-Language Pretraining. CoRR abs/2210.17322 (2022) - [i16]Benjin Zhu, Zhe Wang, Shaoshuai Shi, Hang Xu, Lanqing Hong, Hongsheng Li:
ConQueR: Query Contrast Voxel-DETR for 3D Object Detection. CoRR abs/2212.07289 (2022) - 2021
- [c9]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. AAAI 2021: 6705-6713 - [c8]Fengwei Zhou, Jiawei Li, Chuanlong Xie, Fei Chen, Lanqing Hong, Rui Sun, Zhenguo Li:
MetaAugment: Sample-Aware Data Augmentation Policy Learning. AAAI 2021: 11097-11105 - [c7]Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu:
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning. CVPR 2021: 5383-5392 - [c6]Kai Chen, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung:
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving. ICCV 2021: 7526-7534 - [c5]Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li:
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization. ICCV 2021: 8300-8309 - [c4]Muhammad Awais, Fengwei Zhou, Hang Xu, Lanqing Hong, Ping Luo, Sung-Ho Bae, Zhenguo Li:
Adversarial Robustness for Unsupervised Domain Adaptation. ICCV 2021: 8548-8557 - [c3]Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang:
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. ICML 2021: 651-661 - [c2]Jichao Wang, Ran Zhang, Guanqiang Qi, Lanqing Hong:
A Heuristic-IRM Method on Hard Disk Failure Prediction in Out-of-distribution Environments. IEEM 2021: 1661-1664 - [c1]Jianhua Han, Xiwen Liang, Hang Xu, Kai Chen, Lanqing Hong, Jiageng Mao, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Xiaodan Liang, Chunjing Xu:
SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving. NeurIPS Datasets and Benchmarks 2021 - [i15]Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu:
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning. CoRR abs/2101.00407 (2021) - [i14]Qijun Luo, Zhili Liu, Lanqing Hong, Chongxuan Li, Kuo Yang, Liyuan Wang, Fengwei Zhou, Guilin Li, Zhenguo Li, Jun Zhu:
Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation. CoRR abs/2101.01400 (2021) - [i13]Dapeng Hu, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Alfred Shen, Jiashi Feng:
How Well Self-Supervised Pre-Training Performs with Streaming Data? CoRR abs/2104.12081 (2021) - [i12]Nanyang Ye, Kaican Li, Lanqing Hong, Haoyue Bai, Yiting Chen, Fengwei Zhou, Zhenguo Li:
OoD-Bench: Benchmarking and Understanding Out-of-Distribution Generalization Datasets and Algorithms. CoRR abs/2106.03721 (2021) - [i11]Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan:
Contextualizing Multiple Tasks via Learning to Decompose. CoRR abs/2106.08112 (2021) - [i10]Jianhua Han, Xiwen Liang, Hang Xu, Kai Chen, Lanqing Hong, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Xiaodan Liang, Chunjing Xu:
SODA10M: Towards Large-Scale Object Detection Benchmark for Autonomous Driving. CoRR abs/2106.11118 (2021) - [i9]Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng:
Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision. CoRR abs/2107.09249 (2021) - [i8]Kai Chen, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung:
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving. CoRR abs/2108.12178 (2021) - [i7]Muhammad Awais, Fengwei Zhou, Hang Xu, Lanqing Hong, Ping Luo, Sung-Ho Bae, Zhenguo Li:
Adversarial Robustness for Unsupervised Domain Adaptation. CoRR abs/2109.00946 (2021) - [i6]Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li:
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization. CoRR abs/2109.02038 (2021) - [i5]Kaichen Zhou, Lanqing Hong, Shoukang Hu, Fengwei Zhou, Binxin Ru, Jiashi Feng, Zhenguo Li:
DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture. CoRR abs/2109.05765 (2021) - 2020
- [i4]Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang:
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. CoRR abs/2010.08258 (2020) - [i3]Bochao Wang, Hang Xu, Jiajin Zhang, Chen Chen, Yixing Xu, Xiaozhi Fang, Ning Kang, Lanqing Hong, Chenhan Jiang, Xinyue Cai, Jiawei Li, Fengwei Zhou, Yong Li, Zhicheng Liu, Xinghao Chen, Kai Han, Han Shu, Dehua Song, Yunhe Wang, Wei Zhang, Chunjing Xu, Zhenguo Li, Wenzhi Liu, Tong Zhang:
VEGA: Towards an End-to-End Configurable AutoML Pipeline. CoRR abs/2011.01507 (2020) - [i2]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. CoRR abs/2012.09382 (2020) - [i1]Fengwei Zhou, Jiawei Li, Chuanlong Xie, Fei Chen, Lanqing Hong, Rui Sun, Zhenguo Li:
MetaAugment: Sample-Aware Data Augmentation Policy Learning. CoRR abs/2012.12076 (2020)
2010 – 2019
- 2019
- [j2]Lanqing Hong
, Qingqing Zhai, Xin Wang, Zhi-Sheng Ye:
System Reliability Evaluation Under Dynamic Operating Conditions. IEEE Trans. Reliab. 68(3): 800-809 (2019) - 2018
- [j1]Qingqing Zhai, Piao Chen, Lanqing Hong, Lijuan Shen:
A random-effects Wiener degradation model based on accelerated failure time. Reliab. Eng. Syst. Saf. 180: 94-103 (2018)
Coauthor Index
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last updated on 2023-03-23 23:48 CET by the dblp team
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