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.
Office: Room 150, School of Computer Science and Engineering, Southeast University Jiulonghu Campus, Nanjing, Jiangsu, China.
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, CVPR，IROS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。
My research interests mainly focus on computer vision, specifically on developing multi-modal visual learning schemes and perception and understanding models. These include:
· Developing methods for learning, selecting, and fusing multi-modal data (such as RGB-D, 3D point cloud, and event data) to improve the accuracy and generalization ability of multi-modal visual 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 tasks, including computational visual attention modeling, foreground detection, semantic segmentation and action recognition.
To date, I have no quotas for foreign students.
1. 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)
2. 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)
3. 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)
4. Yongjian Deng#, Hao Chen#, and Youfu Li*. MVF-Net: A multi-view fusion network for event-based object classification. IEEE Transactions on Circuits and Systems for Video Technology, 2021. (JCR Q1)
5. 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)
6. 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)
7. 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 A, ESI高被引论文)
8. 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 Q1, ESI高被引论文)
9. 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)
10. 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)
11. 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)