魯繼文，男，博士，畢業新加坡南洋理工大學，現任清華大學副教授。
基本介紹
- 中文名：魯繼文
- 學位/學歷：博士
- 職業：教師
- 專業方向：計算機視覺、機器學習、智慧型機器人
人物經歷,研究領域,獎勵與榮譽,學術成果,
人物經歷
教育背景
1999年9月至2003年6月 在西安理工大學機械設計製造及其自動化專業學習，獲工學學士學位
2003年9月至2006年4月 在西安理工大學信號與信息處理專業學習，獲工學碩士學位
2007年8月至2011年2月 在新加坡南洋理工大學電氣與電子工程專業學習，獲哲學博士學位
工作履歷
2003年7月至2007年7月 西安理工大學信息科學系 助教
2011年3月至2015年11月 美國伊利諾伊大學香檳分校新加坡高等研究院 研究科學家
2015年11月至今 清華大學自動化系 副教授
學術兼職
IEEE高級會員，2015年至今
Pattern Recognition Letters主編，2019年-
IEEE Transactions on Image Processing編委，2018年至今
IEEE Transactions on Circuits and Systems for Video Technology編委，2018年至今
IEEE Transactions on Biometrics, Behavior, and Identity Science編委，2018年至今
Pattern Recognition編委，2017年至今
Journal of Visual Communication and Image Representation 編委，2017年至今
Pattern Recognition Letters編委，2015年-2018年
Neurocomputing編委，2015年-2018年
IEEE Access編委，2015年-2018年
IEEE電路與系統學會視覺信號處理與通信技術委員會委員，2019年至今
IEEE信號處理學會多媒體信號處理技術委員會委員，2018年至今
IEEE電路與系統學會多媒體系統與套用技術委員會委員，2017年至今
IEEE信號處理學會信息取證與防偽技術委員會委員，2016年-2018年
研究領域
計算機視覺、機器學習、智慧型機器人
研究概況
1.國家自然科學基金聯合重點基金，面向服務機器人的人體動作分析與識別，2019.1-2022.12，主持
2.國家自然科學基金優秀青年基金，視覺模式分析與識別，2019.1-2021.12，主持
3.國家重點研發計畫課題，非神經網路結構的深度學習模型與方法，2018.5-2023.4，主持
4.國家自然科學基金面上項目，面向視覺目標識別的深度度量學習方法研究，2017.1-2020.12，主持
獎勵與榮譽
1.國家優秀青年科學基金獲得者，2018
2.IEEE ICME 2018鉑金最佳論文獎，2018
2023年11月22日，入選美國電子電氣工程師學會發布的2024年IEEE Fellow名單。
學術成果
期刊論文
1.Hao Liu, Jiwen Lu, Minghao Guo, Suping Wu, and Jie Zhou, Learning reasoning-decision networks for robust face alignment, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
2.Venice Erin Liong, Jiwen Lu, Ling-Yu Duan, and Yap-Peng Tan, Deep variational and structural hashing, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
3.Yongming Rao, Jiwen Lu, Ji Lin, and Jie Zhou, Runtime network routing for efficient image classification, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
4.Yueqi Duan, Jiwen Lu, Ziwei Wang, Jianjiang Feng, and Jie Zhou, Learning deep binary descriptor with multi-quantization, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
5.Kevin Lin, Jiwen Lu, Chu-Song Chen, Jie Zhou, and Ming-Ting Sun, Unsupervised deep learning of compact binary descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
6.Yongming Rao, Jiwen Lu, and Jie Zhou, Learning discriminative aggregation network for video-based face recognition and person re-identification, International Journal of Computer Vision, 2019.
7.Guangyi Chen, Jiwen Lu, Ming Yang, and Jie Zhou, Spatial-temporal attention-aware learning for video-based person re-identification, IEEE Transactions on Image Processing, 2019, accepted.
8.Yansong Tang, Jiwen Lu, Zian Wang, Ming Yang, and Jie Zhou, Learning semantics-preserving attention and contextual interaction for group activity recognition, IEEE Transactions on Image Processing, 2019, accept with minor revision.
9.Liangliang Ren, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Uniform and variational deep learning for RGB-D object recognition and person re-identification, IEEE Transactions on Image Processing, 2019, accept with minor revision.
10.Chunze Lin, Jiwen Lu, and Jie Zhou, Multi-grained deep feature learning for robust pedestrian detection, IEEE Transactions on Circuits and Systems for Video Technology, 2018, accepted.
11.Yansong Tang, Zian Wang, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Multi-stream deep neural networks for RGB-D egocentric action recognition, IEEE Transactions on Circuits and Systems for Video Technology, 2018, accepted.
12.Hao Liu, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Ordinal deep learning for facial age estimation, IEEE Transactions on Circuits and Systems for Video Technology, 2018, accepted.
13.Hao Liu, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Two-stream transformer networks for video-based face alignment, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 1, pp. 2546-2554, 2018.
14.Jiwen Lu, Venice Erin Liong, and Jie Zhou, Simultaneous local binary feature learning and encoding for homogeneous and heterogeneous face recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 8, pp. 1979-1993, 2018.
15.Yueqi Duan, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Context-aware local binary feature learning for face recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1139-1153, 2018.
16.Junlin Hu, Jiwen Lu, and Yap-Peng Tan, Sharable and individual multi-view metric learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 9, pp. 2281-2288, 2018.
17.Yueqi Duan, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Deep localized metric learning, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2644-2656, 2018.
18.Junlin Hu, Jiwen Lu, Yap-Peng Tan, Junsong Yuan, and Jie Zhou, Local large-margin multi-metric learning for face and kinship verification, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 8, pp. 1875-1891, 2018.
19.Zhixiang Chen, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Nonlinear structural hashing for scalable video search, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 6, pp. 1421-1433, 2018.
20.Yueqi Duan, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Topology preserving structural matching for partial face recognition, IEEE Transactions on Information Forensics and Security, vol. 13, no. 7, pp. 1823-1837, 2018.
21.Hao Liu, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Label-sensitive deep metric learning for facial age estimation, IEEE Transactions on Information Forensics and Security, vol. 13, no. 2, pp. 292-305, 2018.
22.Shan Gu, Jianfeng Feng, Jiwen Lu, and Jie Zhou, Efficient rectification of distorted fingerprints, IEEE Transactions on Information Forensics and Security, vol. 13, no. 1, pp. 156-169, 2018.
23.Zhe Cui, Jianjiang Feng, Shihao Li, Jiwen Lu, and Jie Zhou, 2D phase demodulation for deformable fingerprint registration, IEEE Transactions on Information Forensics and Security, vol. 13, no. 12, pp. 3153-3165, 2018.
24.Jiwen Lu, Junlin Hu, and Jie Zhou, Deep metric learning for visual understanding, IEEE Signal Processing Magazine, vol. 13, no. 1, pp. 156-169, 2017.
25.Jiwen Lu, Venice Erin Liong, and Jie Zhou, Deep hashing for scalable image search, IEEE Transactions on Image Processing, vol. 26, no. 5, pp. 2352-2367, 2017.
26.Jiwen Lu, Gang Wang, and Jie Zhou, Simultaneous feature and dictionary learning for image set based face recognition, IEEE Transactions on Image Processing, vol. 26, no. 8, pp. 4042-4054, 2017.
27.Jiwen Lu, Junlin Hu, and Yap-Peng Tan, Discriminative deep metric learning for face and kinship verification, IEEE Transactions on Image Processing, vol. 26, no. 9, pp. 4269-4282, 2017.
28.Yueqi Duan, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Learning rotation-invariant local binary descriptor, IEEE Transactions on Image Processing, vol. 26, no. 8, pp. 3636-3651, 2017.
29.Hao Liu, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Learning deep sharable and structural detectors for face alignment, IEEE Transactions on Image Processing, vol. 26, no. 4, pp. 1666-1678, 2017.
30.Zhixiang Chen, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Nonlinear discrete hashing, IEEE Transactions on Multimedia, vol. 19, no. 1, pp. 123-135, 2017.
31.Zhixiang Chen, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Nonlinear sparse hashing, IEEE Transactions on Multimedia, vol. 19, no. 9, pp. 1996-2009, 2017.
32.Venice Erin Liong, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, Deep video hashing, IEEE Transactions on Multimedia, vol. 19, no. 6, pp. 1209-1219, 2017.
33.Venice Erin Liong, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, Deep coupled metric learning for cross-modal matching, IEEE Transactions on Multimedia, vol. 19, no. 6, pp. 1234-1244, 2017.
34.Xi Peng, Jiwen Lu, Zhan Yi, and Rui Yan, Automatic subspace learning via principal coefficients embedding, IEEE Transactions on Cybernetics, vol. 47, no. 11, pp. 3583-3596, 2017.
35.Yuebin Wang, Liqiang Zhang, Hao Deng, Jiwen Lu, Haiyang Huang, Liang Zhang, Jun Liu, Hong Tang, and Xiaoyun Xing, Learning a discriminative distance metric with label consistence for scene classification, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 8, pp. 4427-4440, 2017.
36.Renliang Weng, Jiwen Lu, and Yap-Peng Tan, Robust point set matching for partial face recognition, IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1163-1176, 2016.
37.Junlin Hu, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, Deep transfer metric learning, IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5576-5588, 2016.
38.Rahul Rama Varior, Gang Wang, Jiwen Lu, and Ting Liu, Learning invariant color features for person reidentification, IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3395-3410, 2016.
39.Jiwen Lu, Gang Wang, and Pierre Moulin, Localized multifeature metric learning for image set based face recognition, IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 3, pp. 529-540, 2016.
40.Junlin Hu, Jiwen Lu, and Yap-Peng Tan, Deep metric learning for visual tracking, IEEE Transactions on Circuits and Systems for Video Technology, vol. 26, no. 11, 2056-2068, 2016.
41.Renliang Weng, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, Learning cascaded deep auto-encoder networks for face alignment, IEEE Transactions on Multimedia, vol. 18, no. 10, pp. 2066-2078, 2016.
42.Jiwen Lu, Venice Erin Liong, Xiuzhuang Zhou, and Jie Zhou, Learning compact binary face descriptor for face recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 10, pp. 2041-2056, 2015.
43.Jiwen Lu, Venice Erin Liong, and Jie Zhou, Cost-sensitive local binary feature learning for facial age estimation, IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5356-5368, 2015.
44.Anran Wang, Jiwen Lu, Jianfei Cai, Gang Wang, and Tat-Jen Cham, Unsupervised joint feature learning and encoding for RGB-D scene labeling, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4459-4473, 2015.
45.Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, and Yi Ma, PCANet: A simple deep learning baseline for image classification?, IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5017-5032, 2015.
46.Jiwen Lu, Venice Erin Liong, Gang Wang, and Pierre Moulin, Joint feature learning for face recognition, IEEE Transactions on Information Forensics and Security, vol. 10, no. 7. pp. 1371-1383, 2015.
47.Jiwen Lu, Gang Wang, Weihong Deng, and Kui Jia, Reconstruction-based metric learning for unconstrained face verification, IEEE Transactions on Information Forensics and Security, vol. 10, no. 1, pp. 79-89, 2015.
48.Yi Jin, Jiwen Lu, and Qiuqi Ruan, Coupled discriminative feature learning for heterogeneous face recognition, IEEE Transactions on Information Forensics and Security, vol. 10, no. 3, pp. 640-652, 2015.
49.Sheng Huang, Ahmed Elgammal, Jiwen Lu, and Dan Yang, Cross-speed gait recognition using speed-invariant gait templates and globality-locality preserving projections, IEEE Transactions on Information Forensics and Security, vol. 10, no. 10, pp. 2071-2083, 2015.
50.Shenghua Gao, Yuting Zhang, Kui Jia, Jiwen Lu, and Yingying Zhang, Single sample face recognition via learning deep supervised autoencoders, IEEE Transactions on Information Forensics and Security, vol. 10, no. 10, pp. 2108-2118, 2015.
51.Anran Wang, Jiwen Lu, Jianfei Cai, Tat-Jen Cham and Gang Wang, Large-margin multi-modal deep learning for RGB-D object recognition, IEEE Transactions on Multimedia, vol. 17, no. 11, pp. 1887-1898, 2015.
52.Abrar H. Abdulnabi, Gang Wang, Jiwen Lu, and Kui Jia, Multi-task CNN models for attribute prediction, IEEE Transactions on Multimedia, vol. 17, no. 11, pp.1949-1959, 2015.
53.Haibin Yan, Jiwen Lu, and Xiuzhuang Zhou, Prototype-based discriminative feature learning for kinship verification, IEEE Transactions on Cybernetics, vol. 45, no. 11, pp. 2535-2545, 2015.
54.Jiwen Lu, Xiuzhuang Zhou, Yap-Peng Tan, Yuanyuan Shang, and Jie Zhou, Neighborhood repulsed metric learning for kinship verification, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 2, pp. 331-345, 2014.
55.Jiwen Lu, Gang Wang, and Pierre Moulin, Human identity and gender recognition from gait sequences with arbitrary walking directions, IEEE Transactions on Information Forensics and Security, vol. 9, no. 1, pp. 51-61, 2014.
56.Weihong Deng, Jiani Hu, Jiwen Lu, and Jun Guo, Transform-invariant PCA: A unified approach to fully automatic face alignment, representation, and recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 6, pp. 1275-1284, 2014.
57.Haibin Yan, Jiwen Lu, Weihong Deng, and Xiuzhuang Zhou, Discriminative multimetric learning for kinship verification, IEEE Transactions on Information Forensics and Security, vol. 9, no. 7, pp. 1169-1178, 2014.
58.Jiwen Lu, Yap-Peng Tan, and Gang Wang, Discriminative multimanifold analysis for face recognition from a single training sample per person, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 1, pp. 39-51, 2013.
59.Jiwen Lu, Yap-Peng Tan, Gang Wang, and Gao Yang, Image-to-set face recognition using locality repulsion projections and sparse reconstruction-based similarity measure, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 6, pp. 1070-1080, 2013.
60.Jiwen Lu and Yap-Peng Tan, Cost-sensitive subspace analysis and extensions for face recognition, IEEE Transactions on Information Forensics and Security, vol. 8, no. 3, pp. 510-519, 2013.
61.Jiwen Lu and Yap-Peng Tan, Ordinary preserving manifold analysis for human age and head pose estimation, IEEE Transactions on Human-Machine Systems, vol. 43, no. 2, pp. 249-258, 2013.
62.Jiwen Lu, Xiuzhuang Zhou, Yap-Peng Tan, Yuanyuan Shang, and Jie Zhou, Cost-sensitive semi-supervised discriminant analysis for face recognition, IEEE Transactions on Information Forensics and Security, vol. 7, no. 3, pp. 944-953, 2012.
63.Xiuzhuang Zhou, Yao Lu, Jiwen Lu, and Jie Zhou, Abrupt motion tracking via intensively adaptive markov-chain monte carlo sampling, IEEE Transactions on Image Processing, vol. 21, no. 2, pp. 789-801, 2012.
64.Jiwen Lu and Yap-Peng Tan, Gait-based human age estimation, IEEE Transactions on Information Forensics and Security, vol. 5, no. 4, pp. 761-770, 2010.
65.Jiwen Lu and Yap-Peng Tan, A doubly weighted approach for appearance-based subspace learning methods, IEEE Transactions on Information Forensics and Security, vol. 5, no. 1, pp. 71-81, 2010.
66.Jiwen Lu and Yap-Peng Tan, Regularized locality preserving projections and its extensions for face recognition, IEEE Transactions on Systems, Mans, and Cybernetics, Part B, vol. 40, no. 3, pp. 958-963, 2010.
會議論文
67.Wenzhao Zheng, Zhaodong Chen, Jiwen Lu, and Jie Zhou, Hardness-aware deep metric learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019. (oral)
68.Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, Jie Zhou, COIN: A large-scale dataset for comprehensive instructional video analysis, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
69.Yueqi Duan, Jiwen Lu, and Jie Zhou, UniformFace: Learning deep Equidistributed representation for face recognition, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
70.Yueqi Duan, Lei Chen, Jiwen Lu, and Jie Zhou, Deep embedding learning with discriminative sampling policy, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
71.Yueqi Duan, Yu Zheng, Jiwen Lu, Jie Zhou, and Qi Tian, Structural relational reasoning of point clouds, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
72.Wanhua Li, Jiwen Lu, Jianjiang Feng, Chunjing Xu, Jie Zhou, and Qi Tian, BridgeNet: A continuity-aware probabilistic network for age estimation, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
73.Yongming Rao, Jiwen Lu, and Jie Zhou, Spherical fractal convolution neural networks for point cloud recognition, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
74.Lijie Liu, Jiwen Lu, Chunjing Xu, Qi Tian, Jie Zhou, Deep relational reasoning network for monocular 3D object Detection, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
75.Ziwei Wang, Jiwen Lu, Chenxin Tao, Jie Zhou, and Qi Tian, Learning channel-wise interactions for binary convolutional neural networks, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
76.Xin Yuan, Liangliang Ren, Jiwen Lu, and Jie Zhou, Enhanced Bayesian Compression via Deep Reinforcement Learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
77.Shaohui Liu, Yi Wei, Wang Zhao, and Jiwen Lu, Conditional single-view shape generation for multi-view stereo reconstruction, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Bench, June, 2019.
78.Minghao Guo, Jiwen Lu, and Jie Zhou, Dual-agent deep reinforcement learning for deformable face tracking, European Conference on Computer Vision, Munich, Sep., 2018. (oral)
79.Chunze Lin, Jiwen Lu, Gang Wang, and Jie Zhou, Graininess-aware deep feature learning for pedestrian detection, European Conference on Computer Vision, Munich, Sep., 2018.
80.Liangliang Ren, Jiwen Lu, Zifeng Wang, Qi Tian, Qi Tian, and Jie Zhou, Collaborative deep reinforcement learning for multi-object tracking, European Conference on Computer Vision, Munich, Sep., 2018.
81.Lei Chen, Jiwen Lu, Zhanjie Song, and Jie Zhou, Part-activated deep reinforcement learning for action prediction, European Conference on Computer Vision, Munich, Sep., 2018.
82.Xin Yuan, Liangliang Ren, Jiwen Lu, and Jie Zhou, Relaxation-free dep hashing via policy gradient, European Conference on Computer Vision, Munich, Sep., 2018.
83.Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, and Jie Zhou, Deep reinforcement learning with iterative shift for visual tracking, European Conference on Computer Vision, Munich, Sep., 2018.
84.Xudong Lin, Yueqi Duan, Jiwen Lu, and Jie Zhou, Deep variational metric learning, European Conference on Computer Vision, Munich, Sep., 2018.
85.Yueqi Duan, Wenzhao Zheng, Xudong Lin, Jiwen Lu, and Jie Zhou, Deep adversarial metric learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Salt Lake, June, 2018.
86.Yueqi Duan, Ziwei Wang, Jiwen Lu, Xudong Lin, and Jie Zhou, GraphBit: bitwise interaction mining via deep reinforcement learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Salt Lake, June, 2018.
87.Zhixiang Chen, Xin Yuan, Jiwen Lu, Qi Tian, and Jie Zhou, Deep hashing by discrepancy minimization, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Salt Lake, June, 2018.
88.Yansong Tang, Yi Tian, Jiwen Lu, Peiyang Li, and Jie Zhou, Deep progressive reinforcement learning for skeleton-based action recognition, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Salt Lake, June, 2018.
89.Yongming Rao, Dahua Lin, Jiwen Lu, and Jie Zhou, Learning globally optimized object detector via policy gradient, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Salt Lake, June, 2018.
90.Ji Lin, Yongming Rao, Jiwen Lu, and Jie Zhou, Runtime neural pruning, Advances in Neural Information Processing Systems, Long Bench, Dec., 2017.
91.Yongming Rao, Jiwen Lu, and Jie Zhou, Attention-aware deep reinforcement learning for video based face recognition, IEEE International Conference on Computer Vision, Venice, Oct., 2017.
92.Yongming Rao, Ji Lin, Jiwen Lu, and Jie Zhou, Learning discriminative aggregation networks for video-based face recognition, IEEE International Conference on Computer Vision, Venice, Oct., 2017.
93.Venice Erin Liong, Jiwen Lu, Yap-Peng Tan, and Jie Zhou, Cross-modal deep variational hashing, IEEE International Conference on Computer Vision, Venice, Oct., 2017.
94.Fangyu Liu, Shuaipeng Li, Liqiang Zhang, Chenghu Zhou, Rongtian Ye, Yuebin Wang and Jiwen Lu, 3DCNN-DQN-RNN: A deep reinforcement learning framework for semantic parsing of large-scale 3D point clouds, IEEE International Conference on Computer Vision, Venice, Oct., 2017.
95.Yueqi Duan, Jiwen Lu, Ziwei Wang, Jianjiang Feng, and Jie Zhou, Learning deep binary descriptor with multi-quantization, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Honolulu, July, 2017.
96.Ji Lin, Liangliang Ren, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Consistent-aware deep learning for person re-identification in a camera network, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2017.
97.Rahul Rama Varior, Bing Shuai, Jiwen Lu, Dong Xu, and Gang Wang, A Siamese long short term memory architecture for human re-Identification, European Conference on Computer Vision, Amsterdam, Oct., 2016.
98.Kevin Lin, Jiwen Lu, Chu-Song Chen, and Jie Zhou, Learning compact binary descriptors with unsupervised deep neural networks, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Las Vegas, Jun., 2016.
99.Anran Wang, Jianfei Cai, Jiwen Lu, and Tat Jen Cham, Modality and component aware feature fusion for RGB-D scene classification, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Las Vegas, Jun., 2016.
100.Jiwen Lu, Venice Erin Liong, and Jie Zhou, Simultaneous local binary feature learning and encoding for face recognition, IEEE International Conference on Computer Vision, Santiago, Dec, 2015.
101.Lin Ma, Jiwen Lu, Jianjiang Feng, and Jie Zhou, Multiple feature fusion via weighted entropy for visual tracking, IEEE International Conference on Computer Vision, Santiago, Dec, 2015.
102.Anran Wang, Jianfei Cai, Jiwen Lu, and Tat Jen Cham, MMSS: Multi-modal sharable and specific feature learning for RGB-D object recognition, IEEE International Conference on Computer Vision, Santiago, Dec, 2015.
103.Xianglong Liu, Lei Huang, Cheng Deng, Jiwen Lu, and Bo Lang, Multi-view complementary hash tables for nearest neighbor search, IEEE International Conference on Computer Vision, Santiago, Dec., 2015.
104.Lin Ma, Xiaoqin Zhang, Weiming Hu, Junliang Xing, Jiwen Lu, and Jie Zhou, Local subspace collaborated tracking, IEEE International Conference on Computer Vision, Santiago, Dec., 2015.
105.Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, and Jie Zhou, Multi-manifold deep metric learning for image set classification, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Boston, Jun., 2015.
106.Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, and Jie Zhou, Deep hashing for compact binary codes learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Boston, Jun., 2015.
107.Junlin Hu, Jiwen Lu, and Yap-Peng Tan, Deep transfer metric learning, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Boston, Jun., 2015.
108.Jiwen Lu, Gang Wang, Weihong Deng, and Pierre Moulin, Simultaneous feature and dictionary learning for image set based face recognition, European Conference on Computer Vision, Zurich, Sep., 2014.
109.Tzu-Yi Hung, Jiwen Lu, Yap-Peng Tan, and Shenghua Gao, Efficient sparse estimation via marginal-lasso coding, European Conference on Computer Vision, Zurich, Sep., 2014.
110.Anran Wang, Jiwen Lu, Gang Wang, Jianfei Cai, and Tat-Jen Cham, Multi-modal unsupervised feature learning for RGB-D scene labeling, European Conference on Computer Vision, Zurich, Sep., 2014.
111.Junlin Hu, Jiwen Lu, and Yap-Peng Tan, Discriminative deep metric learning for face verification in the wild, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Columbus, Jun., 2014.
112.Jiwen Lu, Gang Wang, and Pierre Moulin, Image set classification using holistic multiple order statistics features and localized multi-kernel metric learning, IEEE International Conference on Computer Vision, Sydney, Dec., 2013.
113.Renliang Weng, Jiwen Lu, Junlin Hu, Gao Yang, and Yap-Peng Tan, Robust feature set matching for partial face recognition, IEEE International Conference on Computer Vision, Sydney, Dec., 2013.
114.Jiwen Lu, Junlin Hu, Xiuzhuang Zhou, Yuanyuan Shang, Yap-Peng Tan, and Gang Wang, Neighborhood repulsed metric learning for kinship verification, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Providnece, Jun., 2012.
115.Jiwen Lu, Yap-Peng Tan, and Gang Wang, Discriminative multi-manifold analysis for face recognition from a single training sample per person, IEEE International Conference on Computer Vision, Barcelona, Nov., 2011.
116.Jiwen Lu and Yap-Peng Tan, Cost-sensitive subspace learning for face recognition, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, Jun., 2010.
