FACULTY & RESEARCH

Di Hu
Tenure-track Assistant Professor
Di Hu is tenure-track faculty at Gaoling School of Artificial Intelligence, Renmin University of China. Before that, he was previously a research scientist at Baidu Research. He obtained the PhD degree from Northwestern Polytechnical University, supervised by Xuelong Li and Feiping Nie. His research interests are mainly about machine multimodal perception and learning. He has published over 10 papers on top-tier conferences and journals in artificial intelligence, e.g., CVPR, ICCV, ECCV, AAAI etc. He received the 2019 ACM XI’AN Doctoral Dissertation Award, the 2020 CAAI Doctoral Dissertation Award. He served as the program committee of several conferences, e.g., CVPR, ICCV, ECCV, NeurIPS, AAAI etc.

Personal Homepage： https://gsai.ruc.edu.cn/addons/teacher/index/info.html?user_id=13&ruccode=20200218&ln=en

Detailed Information

Education

2014-2019 Ph.D Candidate Northwestern Polytechnical University

2010-2014 B.S. Honors College, Northwestern Polytechnical University

Professional Experience

2020-Now Assistant Professor, Renmin University of China

2019-2020 Research Scientist, Baidu Research

Research Interests

Machine Multimodal Perception and Learning: Mining and exploring the potential problems and methods of multimodal messages (such as image, sound, touch etc.) in the direction of machine perception, reasoning and understanding, then equipping the machines with “multisensory cognitive ability”.

Requirements for Candidates

Curious about things surrounding, self-driven, aiming to do interesting, meaningful and valuable research

Publication:

1、Di Hu, Xuhong Li, Lichao Mou, Pu Jin, Dong Chen, Liping Jing, Xiaoxiang Zhu, and Dejing Dou, Cross-Task Transfer for Multimodal Aerial Scene Recognition, In Proceedings of the European Conference on Computer Vision (ECCV), 2020.

2、Rui Qian, Di Hu, Heinrich Dinkel, Mengyue Wu, Ning Xu, and Weiyao Lin, Learning to Visually Localize Multiple Sound Sources via A Two-stage Manner, In Proceedings of the European Conference on Computer Vision (ECCV), 2020.

3、Di Hu, Feiping Nie, and Xuelong Li, Deep Linear Discriminant Analysis Hashing, Sci Sin Inform, 2019. (CCF A)

4、Di Hu, Feiping Nie, and Xuelong Li, Deep Multimodal Clustering for Unsupervised Audiovisual Learning, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A)

5、Di Hu, Dong Wang, Feiping Nie, Qi Wang, and Xuelong Li, Listen to the Image, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A)

6、Di Hu, Chengze Wang, Feiping Nie, and Xuelong Li, Dense Multimodal Fusion for Hierarchically Joint Representation, In Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019.

7、Di Hu, Feiping Nie, and Xuelong Li, Discrete Spectral Hashing for Efficient Similarity Retrieval, IEEE Trans. Image Processing (TIP), 2018. (CCF A)

8、Di Hu, Feiping Nie, and Xuelong Li, Deep Binary Reconstruction for Cross-modal Hashing, IEEE Trans. Multimedia (TMM), 2018.

9、Xuelong Li, Di Hu, and Xiaoqiang Lu, Image2song: Song Retrieval via Bridging Image Content and Lyric Words, In Proceedings of the IEEE Conference on Computer Vision (ICCV), 2017. (CCF A)

11、Xuelong Li, Di Hu, and Feiping Nie, Deep Binary Reconstruction for Cross-modal Hashing, In Proceedings of the ACM Conference on Multimedia (ACMMM), 2017. (CCF A)

12、Xuelong Li, Di Hu, and Feiping Nie, Large Graph Hashing with Spectral Rotation, In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2017. (CCF A)

13、Di Hu, Xiaoqiang Lu, and Xuelong Li, Multimodal Learning via Exploring Deep Semantic Similarity, In Proceedings of the ACM Conference on Multimedia (ACMMM), 2016. (CCF A)

14、Di Hu, Xuelong Li, and Xiaoqiang Lu, Temporal Multimodal Learning in Audiovisual Speech Recognition, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (CCF A)

15、Di Hu, Zheng Wang, Haoyi Xiong, Dong Wang, Feiping Nie, and Dejing Dou, Heterogeneous Scene Analysis via Self-supervised Audiovisual Learning, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.

16、Di Hu, Lichao Mou, Qingzhong Wang, Junyu Gao, Yuansheng Hua, Dejing Dou, and Xiaoxiang Zhu, Does Ambient Sound Help? - Audiovisual Crowd Counting, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.

17、Yapeng Tian, Di Hu, Chenliang Xu, Co-Learn Sounding Object Visual Grounding and Visually Indicated Sound Separation in A Cycle, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.

18、Rui Qian, Di Hu, Heinrich Dinkel, Mengyue Wu, Ning Xu, Weiyao Lin, A Two-Stage Framework for Multiple Sound-Source Localization, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2020.

Services

1、Reviewer of Journal: TIP, TKDE, TMM, Neurocomputing

2、Program Committee of Conference: NeurIPS 2020, CVPR 2018 2020, ICCV 2019, ECCV2020, AAAI 2018 2020, ACCV 2018 2020

3、Co-organizer: ICDM 2019 Tutorial on Automated Deep Learning: Theory, Algorithms, Platforms, and Applications

Awards

2020.9 Won the 2020 CAAI Outstanding Doctoral Dissertation Award

2019.8 Selected by the『AIDU』Talent Recruitment Project of Baidu

2019.8 Won the 2019 ACM Xi'an Doctoral Dissertation Award

2019.5 Selected by the CVPR 2019 Doctoral Consortium


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