Picture for Hao Shao

Hao Shao

ReasonNet: End-to-End Driving with Temporal and Global Reasoning

May 17, 2023
Hao Shao, Letian Wang, Ruobing Chen, Steven L. Waslander, Hongsheng Li, Yu Liu

* CVPR 2023

Access Paper or Ask Questions

Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

May 08, 2023
Letian Wang, Jie Liu, Hao Shao, Wenshuo Wang, Ruobing Chen, Yu Liu, Steven L. Waslander

Figure 1 for Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

Figure 2 for Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

Figure 3 for Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

Figure 4 for Efficient Reinforcement Learning for Autonomous Driving with Parameterized Skills and Priors

* Robotics: Science and Systems (RSS 2023)

Access Paper or Ask Questions

Blending Anti-Aliasing into Vision Transformer

Oct 28, 2021
Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia

Figure 1 for Blending Anti-Aliasing into Vision Transformer

Figure 2 for Blending Anti-Aliasing into Vision Transformer

Figure 3 for Blending Anti-Aliasing into Vision Transformer

Figure 4 for Blending Anti-Aliasing into Vision Transformer

* Accepted to NeurIPS 2021

Access Paper or Ask Questions

Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Mar 26, 2021
Guangwei Gao, Hao Shao, Yi Yu, Fei Wu, Meng Yang

Figure 1 for Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Figure 2 for Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Figure 3 for Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Figure 4 for Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

* 9 pages, 6 figures

Access Paper or Ask Questions

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

Aug 26, 2020
Haisheng Su, Jinyuan Feng, Hao Shao, Zhenyu Jiang, Manyuan Zhang, Wei Wu, Yu Liu, Hongsheng Li, Junjie Yan

Figure 1 for Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

Figure 2 for Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

Figure 3 for Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

Figure 4 for Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

* Submitted to CVPR workshop of ActivityNet Challenge 2020

Access Paper or Ask Questions

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

Jun 16, 2020
Siyu Chen, Junting Pan, Guanglu Song, Manyuan Zhang, Hao Shao, Ziyi Lin, Jing Shao, Hongsheng Li, Yu Liu

Figure 1 for 1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

Figure 2 for 1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

Figure 3 for 1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

Figure 4 for 1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

* arXiv admin note: substantial text overlap with arXiv:2006.07976

Access Paper or Ask Questions

Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA

Mar 09, 2020
Xianpei Han, Zhichun Wang, Jiangtao Zhang, Qinghua Wen, Wenqi Li, Buzhou Tang, Qi Wang, Zhifan Feng, Yang Zhang, Yajuan Lu, Haitao Wang, Wenliang Chen, Hao Shao, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang, Kezun Zhang, Meng Wang, Yinlin Jiang, Guilin Qi, Lei Zou, Sen Hu, Minhao Zhang, Yinnian Lin

* 21 pages, in Chinese, 9 figures and 17 tables, CCKS 2019 held an evaluation track about knowledge graph with 6 tasks and attracted more than 1,600 teams

Access Paper or Ask Questions