陈浩
职称:副高
所在院系:计算机科学系
研究方向:计算机视觉,多模态感知与理解
电话:
邮箱:haochen303@seu.edu.cn
职务:
个人简介
研究方向
教育经历
工作经历
科研项目
论文著作
专利
获奖情况

Hao Chen (陈浩)    

Ph.D., Associate Professor

School of Computer Science and Engineering, Southeast University

I am a member of PAttern Learning and Mining(PALM) Lab. 

Email: haochen303@seu.edu.cn

Office: Room 150, School of Computer Science and Engineering, Southeast University Jiulonghu Campus, Nanjing, Jiangsu, China.

 

Brief Biography

Dr. Hao Chen joined the PALM Lab in the School of Computer Science and Engineering, Southeast University as an associate professor in 2021He received the Ph.D. degree from the Robotic Vision Lab in City University of Hong Kong, in 2019. From 2019 to 2020, he worked as a research fellow at Nanyang Technological University, Singapore.  

陈浩,博士,东南大学计算机科学与工程学院PALM实验室副教授,博士生导师,江苏省双创博士、南京市留学择优人才,东南大学紫金青年学者2019年于香港城市大学机器人视觉实验室获博士学位,2019-2020年任新加坡南洋理工大学博士后研究员。迄今在计算机视觉及机器人领域国际权威期刊和会议IJCV, TIP, CVPRIROS等上发表论文20余篇,其中3篇被评为ESI高被引论文(前1%)。主持国家自然科学基金,江苏省自然科学基金多项,长期担任计算机视觉和机器人领域国际知名期刊和会议的审稿人。

Research Interests

My research interests mainly focus on computer vision and multi-modal systems, specifically on developing multi-modal learning and interpretation schemes, multi-modal scene-understanding models, and controlable unimodal/multi-modal AIGC. These include:

·        Developing methods for learning, selecting, and fusing multi-modal data (such as RGB-D, 3D point cloud, event data, and vision-language) to improve the accuracy and generalization ability of multi-modal systems, such as those used in autonomous driving.

·        Developing transfer learning, weakly-supervised learning, and self-supervised learning schemes for multi-modal data.

·        Conducting multi-modal interpretation to gain insights into the working rules of multi-modal systems.

·        Tackling downstream scene understanding and generation tasks, including computational visual attention modeling, semantic segmentation, action recognition and controlable unimodal/multi-modal AIGC for images/videos.

 

  • 欢迎2025年入学的同学加入,还有学硕、专硕及博士名额,招生须知见招生介绍.pdf,欢迎尽快联系!

  • 实验室随时欢迎感兴趣的大二大三学生加入进行科研训练!

  • To date, I have no quotas for foreign students.



Selected Publications #co-first author, *corresponding author

 

1.  Yuhan LiuYongjian DengHao ChenZhen Yang,Video Frame Interpolation via Direct Synthesis with the Event-based Reference. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (CCF A)

2.   Hao Chen, Feihong Shen, Ding Ding, Yongjian Deng, Chao Li, Disentangled Cross-modal Transformer for RGB-D Salient Object Detection and Beyond. IEEE Transactions on Image Processing, 2024. (JCR Q1, CCF A)

3. Yongjian Deng, Hao Chen*, and Youfu Li. A Dynamic GCN with Cross-Representation Distillation for Event-Based Learning. In Annual AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF A)

4.  Yongjian Deng, Hao Chen*, and Youfu Li*. A Voxel Graph CNN for Object Classification with Event Cameras. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (CCF A)

5.   Hao Chen, Youfu Li*, Yongjian Deng, and Guosheng Lin. CNN-based RGB-D salient object detection: learn, select and fuse. International Journal of Computer Vision, 2021, 129 (7), 2076-2096. (JCR Q1, CCF A)

6.  Yongjian Deng#, Hao Chen#, and Youfu Li*. Learning from Images: A Distillation Learning Framework for Event Cameras. IEEE Transactions on Image Processing, 2021, 30, 4919-4931. (JCR Q1, CCF A)

7.  Yongjian Deng#, Hao Chen#, and Youfu Li*. MVF-Net: A multi-view fusion network for event-based object classificationIEEE Transactions on Circuits and Systems for Video Technology, 2021. (JCR Q1)

8.  Hao Chen, Youfu Li*, and Dan Su. Discriminative cross-modal transfer learning and densely cross-level feedback fusion for RGB-D salient object detection. IEEE Transactions on Cybernetics, 50(11): 4808-4820, 2020. (JCR Q1)

9.  Hao Chen, Yongjian Deng, Youfu Li*, Tzu-Yi Hung, and Guosheng Lin*. RGBD salient object detection via disentangled cross-modal fusion. IEEE Transactions on Image Processing, 29:8407–8416, 2020. (JCR Q1, CCF A)

10.  Hao Chen and Youfu Li*. Three-stream attention-aware network for RGB-D salient object detection. IEEE Transactions on Image Processing, 28(6):2825–2835, 2019. (JCR Q1, CCF AESI高被引论文)

11. Hao Chen, Youfu Li*, and Dan Su. Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection. Pattern Recognition, 86:376–385, 2019. (JCR Q1ESI高被引论文)

12. Hao Chen and Youfu Li*. Progressively complementarity-aware fusion network for RGB-D salient object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3051–3060, 2018. (CCF A)

13. Hao Chen, You-Fu Li*, and Dan Su. Attention-aware cross-modal cross-level fusion network for RGB-D salient object detection. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6821–6826. IEEE, 2018. (Top Conference on Robotics)

14. Junwei Han*, Hao Chen, Nian Liu, Chenggang Yan, and Xuelong Li. CNNs-based RGB-D saliency detection via cross-view transfer and multi-view fusion. IEEE Transactions on Cybernetics, 48(11): 3171-3183, 2017. (JCR Q1, ESI高被引论文)

 

Projects

1. 国家自然科学基金青年科学基金项目,2022.01--2024.12,主持

2. 江苏省自然科学基金青年基金项目,2021.07--2024.06,主持

3. 国家自然科学基金国际(地区)合作与交流项目, 2023.01--2026.12,子经费负责人

4. 南京市留学人员科技创新项目,2023.01--2023.12,主持

5. 创新特区项目,2023.12--2024.12,主持



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