General

Qiulei Dong   Ph.D.   Professor        
National Laboratory of Pattern Recognition
Institute of Automation
Chinese Academy of Sciences
Email: qldong@nlpr.ia.ac.cn
Telephone: 62544618 
Postcode: 100190

Research Areas

3D Computer Vision, Pattern Recognition

Education

-- Ph. D.

Experience

   
Work Experience

2016 -- present, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, professor 

2011 -- 2016, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, associate professor

2014 -- 2015, University of California, Los Angeles, USA, visiting scholar

2008 -- 2011, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, assistant professor

Teaching Experience

"Computer Vision" since Spring 2008

Publications

   
Papers

36.B. Liu, Q. Dong*, and Z. Hu, Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning, CVPR, 2021.

35.S. Fan, Q. Dong*, F. Zhu, et al. SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation, CVPR, 2021.

34.S. Deng, B. Liu, and Q. Dong*, Rotation Transformation Network: Learning View-Invariant Point Cloud for Classification and Segmentation, In Proc. IEEE International Conference on Multimedia and Expo (ICME), 2021.

33.D. Wang and Q. Dong*, MCFINet: Multi-Depth Convolution Network with Shallow-Deep Feature Integration for Semantic Labeling in Remote Sensing Images, IEEE Geoscience and Remote Sensing Letters, 2021, accepted.

32.Q. Dong, X. Gao, H. Cui, and Z. Hu, Robust Camera Translation Estimation via Rank Enforcement, IEEE Transactions on Cybernetics, 2020, doi: 10.1109/TCYB.2020.2988679.

31.L. Chang, L. Jin, L. Weng, W. Chao, X. Wang, X. Deng, and Q. Dong*, Face-Sketch Learning with Human Sketch-Drawing Order Enforcement, Science China Information Sciences, 219103:1–219103:3, 2020.

30.Q. Dong, B. Liu, and Z. Hu, Non-uniqueness phenomenon of object representation in modelling IT cortex by deep convolutional neural network (DCNN), Frontiers in Computational Neuroscience, 14:35, 2020.

29.B. Liu, Q. Dong*, Z. Hu, Zero-shot learning from Adversarial feature residual to compact visual feature, AAAI, New York, USA, pp. 11547-11554, 2020.[code]

28.Q. Dong and H. Wang, Latent-Smoothness Nonrigid Structure from Motion by Revisiting Multi-Linear Factorization, IEEE Transactions on Cybernetics, 49(9): 3557-3570, 2019.

27.Q. Dong, J. Sun, and Z. Hu, Face representation by deep learning: a linear encoding in a parameter space? CoRR abs/1910.09768 (2019).

26.T. Zhang, H. Wang, and Q. Dong*, Deep Disentangling Siamese Network for Frontal Face Synthesis under Neutral Illumination, IEEE Signal Processing Letters, 25(9): 1344-1348, 2018.

25.Q. Dong, H. Wang, Z. Hu, Commentary: Using goal-driven deep learning models to understand sensory cortex, Frontiers in Computational Neuroscience, 2018, doi: 10.3389/fncom.2018.00004

24.Q. Dong, H. Wang, Z. Hu, Statistics of visual responses to image object stimuli from primate AIT neurons to DNN neurons, Neural Computation, 30: 447–476, 2018.

23.Q. Dong, M. Shu, H. Cui, H. Xu, Z. Hu, Learning Stratified 3D Reconstruction, SCIENCE CHINA Information Sciences, 61(2): 023101, 2018.

22.Q. Dong, B. Liu, Z. Hu, Comparison of IT neural response statistics by simulations, Frontiers in Computational Neuroscience, 2017, doi: 10.3389/fncom.2017.00060

21.T. Zhang, Q. Dong*, M. Tang, Z. Hu, Two-Stream Deep Correlation Network for Frontal Face Recovery, IEEE Signal Processing Letters, 24(10): 1478-1482, 2017.

20.T. Zhang, R. Qin, Q. Dong, W. Gao, H. Xu, Z. Hu, Physiognomy: Personality Traits Prediction by Learning, International Journal of Automation and Computing, 14(4): 386-395, 2017.

19.Q. Dong*, H. Hu, Sequential factorization for nonrigid structure from motion via LBFGS, In Proc. International Conference on Pattern Recognition, pp. 1731-1736, Cancun, Mexico, 2016.

18.T. Zhang, Q. Dong*, Z. Hu, Pursuing face identity from view-specific representation to view-invariant representation, In Proc. International Conference on Image Processing, pp. 3244-3248, 2016.

17.L. He, Q. Dong*, G. Wang, Fast depth extraction from a single image, International Journal of Advanced Robotic Systems, 2016.

16.L. He, Q. Dong*, Z. Hu, The inherent ambiguity in scene depth learning from singleimages, SCIENTIA SINICA Informationis, 46(7):811-818, 2016.

15.Q. Kong, Y. Zeng, Q. Dong. Biologically inspired deep stereo model. In Proc. IEEE International Conference on Image Processing, 2015.

14.L. Li, Q. Dong, R. Zhao, GLRAMMC: generalized low-rank approximations of matrices with missing components and its applications in image processing, Journal of Computer-Aided Design and Computer Graphics (in Chinese), 27(11): 2065-2076, 2015.

13.K. Shi, Q. Dong, F. Wu, Euclidean upgrading from segment lengths: DLT-like algorithm and its variants. Image and Vision Computing, 32(2): 155-168, 2014.

12.Q. Zhang, Y. Wu, F. Wang, Q. Dong, L. Jiao: Suboptimal Solutions to the Algebraic-Error Line Triangulation. Journal of Mathematical Imaging and Vision 49(3): 611-632, 2014.

11.H. Hao, C. Lei, Q. Dong, Y. Shen, J. Chi, H. Ye, H. Wang, Effects of exogenous methyl jasmonate on the biosynthesis of shikonin derivatives in callus tissues of arnebia euchroma, Applied Biochemistry and Biotechnology, 173 (8): pp.2198-2210, 2014.

10.Q. Dong, L. Li, Smooth incomplete matrix factorization and its applications in image/video denoising, Neurocomputing, 122:458-469, 2013.

9.Q. Dong, Two-dimensional relaxed representation, Neurocomputing, 121:248-253, 2013.[code]

8.K. Shi, Q. Dong, F. Wu, Weighted Similarity-Invariant Linear Algorithm for Camera Calibration With Rotating 1-D Objects. IEEE Transactions on Image Processing, 21(8): 3806-3812, 2012.

7.Q. Dong, Z. Gu, Z. Hu,  Automatic real-time SLAM relocalization based on a hierarchical bipartite graph model, Science China Information Sciences, 55(12): 2841-2848, 2012.

6.Z. Gu, Q. Dong, Z. Hu, A real-time robust monocular SLAM method, Chinese Journal of Computers, in press.

5.Z. Gu, Q. Dong, Monocular SLAM based on partial inertial measurement unit information, Journal of Computer-Aided Design and Computer Graphics, 24(2): 155-160, 2012.

4.Q. Dong, Y. Wu, and Z. Hu. Pointwise Motion Image(PMI): A novel motion representation and its applications to abnormality detection and behavior recognition. IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 3, pp. 409-416, 2009.

3.Q. Dong, Y. Wu, and Z. Hu. Video-based real-time automatic measurement for the height of human body. ACTA AUTOMATICA SINICA (in Chinese), vol. 35, no. 2, pp. 137-144, 2009.

2.Q. Dong, Y. Wu, and Z. Hu. Gesture Segmentation from a Video Sequence Using Greedy Similarity Measure. In Proc. the 18th International Conference on Pattern Recognition, HongKong, China, vol. 1, pp.331-334, 2006.

1.Q. Dong, Y. Wu, and Z. Hu. Gesture Recognition Using Quadratic Curves. In Proc. the 7th Asian Conference on Computer Vision, Hyderabad, India, pp. 817-825, 2006.


Research Interests

3D Computer Vision, Pattern Recognition

Students

已指导学生

陈新泽  硕士研究生  081203-计算机应用技术  

徐梦洋  硕士研究生  085211-计算机技术  

现指导学生

牛李金梁  硕士研究生  081203-计算机应用技术  

陈豹  硕士研究生  081104-模式识别与智能系统  

邓爽  博士研究生  081104-模式识别与智能系统  

王东骥  硕士研究生  085211-计算机技术  

周正铭  硕士研究生  081104-模式识别与智能系统  

孙珈因  博士研究生  081104-模式识别与智能系统