中科院计算所视觉信息处理与学习组
中科院计算所视觉信息处理与学习组
Qianqian Xu

Associate Professor

Research area: data mining, machine learning

Qianqian Xu  is currently an Associate Professor with the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS). She received the Ph.D degree in computer science from the University of Chinese Academy of Sciences under the supervision of Prof. Qingming Huang in 2013, and the B.S. degree in computer science from China University of Mining and Technology in 2007. From 2013 to 2015, she worked in BICMR of Peking University as a postdoctor supervised by Prof. Yuan Yao.  During 2011, She has studied in School of Computer Science and Engineering, Nanyang Technological University, under the supervision of Prof. Weisi Lin.

Experience
Educational experience
  • 2003.9-2007.7 China University of Mining and Technology, B. Eng.
  • 2007.9-2013.7 University of Chinese Academy of Sciences, Ph.D.
Academic experience
  • 2018.03–Present Associate Professor in Institute of Computing Technology, CAS
  • 2015.10-2018.03 Associate Professor in Institute of Information Engineering, CAS
  • 2015.07-2015.10 Assistant Professor in Institute of Information Engineering, CAS
  • 2013.07-2015.07 Postdoctor in Beijing International Center for Mathematical Research, Peking University
Research project

1.   Study on Partial Ranking for Crowdsourced Subjective Visual Property

Project type: NSFC
Project time: 2020/01-2023/12
Project leader: Qianqian Xu

2.   Outlier Detection on Crowdsourced Pairwise Comparisons

Project type: CCF-Tencent
Project time: 2017/10-2018/10
Project leader: Qianqian Xu

3.   Crowdsourcing Strategy based on Geometrical and Topological methods

Project type: NSFC
Project time: 2017/01-2020/12
Project leader: Qianqian Xu

4.   Crowdsourced Data Analysis based on Geometry and Topology

Project type: Beijing
Project time: 2018/1-2020/12
Project leader: Qianqian Xu
Book or Paper

Papers

1.  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan Yao, “From Social to Individuals: a Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation”, IEEE Transactions on Pattern  Analysis and Machine Intelligence, TPAMI, vol. 41, no. 4, pp. 844--856, Apr. 2019. (Regular paper)

2. Zhiyong Yang, Qianqian Xu, Xiaochun Cao and Qingming Huang. "Task-Feature Collaborative Learning with Application to Personalized Attribute Prediction", IEEE Transactions on Pattern Analysis and Machine Intelligence, TPAMI, 2020.  (Early Access)

3.  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, and Yuan Yao, “False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking”, International Conference on Machine Learning, ICML 2016, 1282--1291, New York City, NY, USA, Jun 19-24, 2016. (Oral)

4.  Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, and Yuan Yao, "iSplit LBI: Individualized Partial Ranking with Ties via Split LBI", Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 3896--3906, Vancouver, Canada, December 8-14, 2019. (Poster)

5.  Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, and Yuan Yao, "Deep Robust Subjective Visual Property Prediction in Crowdsourcing", International Conference on Computer Vision and Pattern Recognition, CVPR 2019, 8993--9001, Long Beach, CA, USA, Jun 16-20, 2019.  (Poster)

6.  Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, and Yuan Yao, "A Margin-based MLE for Crowdsourced Partial Ranking", ACM Conference on Multimedia, ACM MM 2018, 591--599, Seoul, Korea, Oct 22-26, 2018. (Full paper) 

7.  Qianqian Xu, Ming Yan, Chendi Huang, Jiechao Xiong, Qingming Huang, and Yuan Yao, “Exploring Outliers in Crowdsourced Ranking for QoE”, ACM Conference on Multimedia, ACM MM 2017, 1540--1548, Mountain View, CA, USA, Oct 23-27, 2017. (Full paper, Oral)

8.  Qianqian Xu, Zhiyong Yang, Zuyao Chen, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao, and Qingming Huang, "Deep Partial Rank Aggregation for Personalized Attributes", AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Feb 2-9, 2021.

9.  Qianqian Xu, Jiechao Xiong, Zhiyong Yang, Xiaochun Cao, Qingming Huang, and Yuan Yao, "Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings", AAAI Conference on Artificial Intelligence, AAAI 2020, NewYork Midtown, New York, USA, Feb 7-12, 2020. (Oral) 

10.  Qianqian Xu, Jiechao Xiong, Xi Chen, Qingming Huang, and Yuan Yao, "HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation", AAAI Conference on Artificial Intelligence, AAAI 2018, 4326--4334, New Orleans, LA, USA, Feb 2-7, 2018. (Oral)

11. Qianqian Xu, Jiechao Xiong, Xiaochun Cao, and Yuan Yao, “Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation”, ACM Conference on Multimedia, ACM MM 2016, 841--850, Amsterdam, The Netherlands, Oct 15-19, 2016. (Full paper) 

12.  Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao, “Robust Evaluation for Quality of Experience in Crowdsourcing”, ACM Conference on Multimedia, ACM MM 2013, 43--52, Barcelona, Spain, Oct 21-25, 2013. (Full paper)

13.  Qianqian Xu, Qingming Huang, and Yuan Yao, “Online Crowdsourcing Subjective Image Quality Assessment”, ACM Conference on Multimedia, ACM MM 2012, 359--368, Nara, Japan, Oct 29 - Nov 02, 2012. (Full paper)

14.  Qianqian Xu, Tingting Jiang, Yuan Yao, Qingming Huang, Bowei Yan, and Weisi Lin, “Random Partial Paired Comparison for Subjective Video Quality Assessment via HodgeRank”, ACM Conference on Multimedia, ACM MM 2011, 393--402, Scottsdale, AZ, USA, Nov 28 - Dec 1, 2011. (Full paper)

15. Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao, “Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation”, IEEE Transactions on Multimedia, vol. 16, no. 2, pp. 373--386, Feb. 2014. (Regular paper)

16. Qianqian Xu, Qingming Huang, Tingting Jiang, Bowei Yan, Weisi Lin, and Yuan Yao, “HodgeRank on Random Graphs for Subjective Video Quality Assessment”, IEEE Transactions on Multimedia, vol. 14, no. 3, pp. 844--857, Jun. 2012. (Regular paper)

17. Zhiyong Yang, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao, and Qingming Huang, "Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer", Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 5846--5857, Vancouver, Canada, December 8-14, 2019. (Poster)

18. Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, and Qingming Huang, "DM2C: Deep Mixed-Modal Clustering", Annual Conference on Neural Information Processing Systems, NeurIPS 2019, 5880--5890, Vancouver, Canada, December 8-14, 2019. (Spotlight)

19. Yangbangyan Jiang, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao, and Qingming Huang, “What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models”, AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Feb 2-9, 2021.

20. Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, and Qingming Huang, “Dual Quaternion Knowledge Graph Embeddings”, AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Feb 2-9, 2021.

21. Zuyao Chen, Qianqian Xu , Runmin Cong, and Qingming Huang, “Global Context-Aware Progressive Aggregation Network for Salient Object Detection”, AAAI Conference on Artificial Intelligence, AAAI 2020, NewYork Midtown, New York, USA, Feb 7-12, 2020. (Oral) 

22. Zhaopeng Li, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao, and Qingming Huang, "Quaternion-Based Knowledge Graph Network for Recommendation", ACM Conference on Multimedia, ACM MM 2020, 880--888, Virtual Event/Seattle, WA, USA, Oct 12-16, 2020.  (Full paper, Oral)

23. Tianwei Cao, Qianqian Xu, Zhiyong Yang, and Qingming Huang, "Task-distribution-aware Meta-learning for Cold-start CTR Prediction", ACM Conference on Multimedia, ACM MM 2020, 3514--3522, Virtual Event/Seattle, WA, USA, Oct 12-16, 2020.  (Full paper)

24. Zhiyong Yang, Qianqian Xu, Xiaochun Cao, and Qingming Huang, "Learning Personalized Attribute Preference via Multi-task AUC Optimization", AAAI Conference on Artificial Intelligence, AAAI 2019, 5660--5667, Honolulu, Hawaii, USA, Jan 27 - Feb 1, 2019. (Oral)

25. Ke Ma, Qianqian Xu, Zhiyong Yang, and Xiaochun Cao, "Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin", AAAI Conference on Artificial Intelligence, AAAI 2019, 2978--2985, Honolulu, Hawaii, USA, Jan 27 - Feb 1, 2019.

26. Ke Ma, Qianqian Xu, and Xiaochun Cao, "Robust Ordinal Embedding from Contaminated Relative Comparisons, AAAI Conference on Artificial Intelligence", AAAI 2019, 7908--7915, Honolulu, Hawaii, USA, Jan 27 - Feb 1, 2019.

27. Zhiyong Yang, Qianqian Xu, Xiaochun Cao, and Qingming Huang, "From Common to Special: When Multi-Attribute Learning Meets Personalized Opinions", AAAI Conference on Artificial Intelligence, AAAI 2018, 515--522, New Orleans, LA, USA, Feb 2-7, 2018.

28. Shilong Bao, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao, and Qingming Huang, "Collaborative Preference Embedding against Sparse Labels", ACM Conference on Multimedia, ACM MM 2019, 2079--2087, Nice, France, Oct 21-25, 2019.  (Full paper, Oral)

29. Zitai Wang, Qianqian Xu, Ke Ma, Yangbangyan Jiang, Xiaochun Cao, and Qingming Huang, "Adversarial Preference Learning with Pairwise Comparisons", ACM Conference on Multimedia, ACM MM 2019, 656--664, Nice, France, Oct 21-25, 2019.   (Full paper, Oral)

30. Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, and Qingming Huang, "Duet Robust Deep Subspace Clustering", ACM Conference on Multimedia, ACM MM 2019, 1596--1604, Nice, France, Oct 21-25, 2019.  (Full paper, Spotlight)

31. Zhiyong Yang, Qianqian Xu, Weigang Zhang, Xiaochun Cao, and Qingming Huang, "Split Multiplicative Multi-view Subspace Clustering", IEEE Transactions on Image Processing, vol. 28, no. 10, pp. 5147-5160, May 2019. (Regular paper)

32. Zhaopeng Li, Qianqian Xu, Yangbangyan Jiang, Ke Ma, Xiaochun Cao, and Qingming Huang, "Neural Collaborative Preference Learning with Pairwise Comparisons", IEEE Transactions on Multimedia, 2020. (Early Access)

33. Peisong Wen, Ruolin Yang, Qianqian Xu, Chen Qian, Qingming Huang, Runmin Cong, and Jianlou Si, "DMVOS: Discriminative Matching for Real-time Video Object Segmentation", ACM Conference on Multimedia, ACM MM 2020, 2048--2056, Virtual Event/Seattle, WA, USA, Oct 12-16, 2020.  (Full paper)

34. Zhenhuan Liu, Liang Li, Shaofei Cai, Jincan Deng, Qianqian Xu, Shuhui Wang, and Qingming Huang, "IR-GAN: Image Manipulation with Linguistic Instruction by Increment Reasoning", ACM Conference on Multimedia, ACM MM 2020, 322--330, Virtual Event/Seattle, WA, USA, Oct 12-16, 2020.  (Full paper)

35. Chongyi Li, Huazhu Fu, Runmin Cong, Zechao Li, and Qianqian Xu, "NuI-Go: Recursive Non-local Encoder-Decoder Network for Retinal Image Non-uniform Illumination Removal", ACM Conference on Multimedia, ACM MM 2020, 1478--1487, Virtual Event/Seattle, WA, USA, Oct 12-16, 2020.  (Full paper)

36. Yangbangyan Jiang, Zhiyong Yang, Qianqian Xu, Xiaochun Cao, and Qingming Huang, "When to Learn What: Deep Cognitive Subspace Clustering", ACM Conference on Multimedia, ACM MM 2018, 718--726, Seoul, Korea, Oct 22-26, 2018. (Full paper)

37. Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, and Yuan Yao, "Stochastic Non-convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size", AAAI Conference on Artificial Intelligence, AAAI 2018, 3738--3745, New Orleans, LA, USA, Feb 2-7, 2018.

38. Wenqi Ren, Sifei Liu, Lin Ma, Qianqian Xu, Xiangyu Xu, Xiaochun Cao, Junping Du, and Ming-Hsuan Yang, "Low-Light Image Enhancement via a Deep Hybrid Network", IEEE Transactions on Image Processing, vol. 28, no. 9, pp. 4364--4375, Sep. 2019. (Regular paper)

39. Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, and Yuan Yao, "Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size", IEEE Transactions on Knowledge and Data Engineering, 2020. (Early Access)

40Zuyao Chen, Runmin Cong, Qianqian Xu, and Qingming Huang, "DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection", IEEE Transactions on Image Processing, 2020. (Early Access)




For more information, please refer to https://qianqianxu010.github.io/




中科院计算所视觉信息处理与学习组
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