视频简介

教育经历

  • 2002年7月,毕业于武汉大学数学与统计学院数学与应用数学专业,获理学学士学位
  • 2005年7月,毕业于北京大学数学科学学院信息科学系,获理学硕士学位
  • 2011年3月,毕业于香港城市大学计算机系,获PhD学位

工作经历

  • 2020年9月—现在,中国人民大学高瓴人工智能学院,教授
  • 2019年8月—2020年8月,中国人民大学信息学院,教授
  • 2013年9月—2019年7月,中国人民大学信息学院,副教授
  • 2011年5月—2013年7月,北京大学计算机所,助理研究员

研究方向

机器学习:元学习,小样本学习,自监督学习,网络结构搜索,机器学习理论
计算机视觉:跨模态对比学习,文生成图,视频自监督表示学习,视频动作迁移,图像语义分割
应用研究:大规模多模态预训练(设计首个公开的中文通用图文预训练模型BriVL)

学生要求

扎实的数学功底,对研究有浓厚兴趣,较好的动手能力。

教授课程

  • 研究生课:《高级机器学习》
  • 本科生课:《统计学习》,《分布式系统与云计算》

科研项目

  • 阿里达摩院合作项目,面向视觉语言的多模态特征学习,2020.09-2021.09,主持
  • 国家自然科学基金面上项目,小样本学习关键问题研究,2020.01-2023.12,主持
  • 国家自然科学基金面上项目,噪声环境下的弱监督图像语义分割研究,2016.01-2019.12,主持
  • 中国人民大学预研委托项目,噪声环境下的弱监督图像语义分割关键问题研究,2015.01-2017.12,主持
  • 国家自然科学基金青年项目,基于图的半监督学习关键问题研究及其在图像理解中的应用,2013.01-2015.12,主持
  • 北京市自然科学基金面上项目,基于稀疏表示的半监督学习新方法及应用研究,2013.01-2015.12,主持

学术成果

2021
Z-Score Normalization, Hubness, and Few-Shot Learning
Nanyi Fei, Yizhao Gao, Zhiwu Lu*, and Tao Xiang
International Conference on Computer Vision (ICCV), 2021. (CCF A)

Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning
Yizhao Gao, Nanyi Fei, Guangzhen Liu, Zhiwu Lu*, and Tao Xiang
37th Conference on Uncertainty in Artificial Intelligence (UAI), 2021.

Self-Supervised Video Representation Learning with Constrained Spatiotemporal Jigsaw
Yuqi Huo, Mingyu Ding, Haoyu Lu, Ziyuan Huang, Mingqian Tang, Zhiwu Lu*, and Tao Xiang
International Joint Conference on Artificial Intelligence (IJCAI), 2021. (CCF A)

A Global Occlusion-Aware Approach to Self-Supervised Monocular Visual Odometry
Yao Lu, Xiaoli Xu, Mingyu Ding, Zhiwu Lu*, and Tao Xiang
AAAI Conference on Artificial Intelligence (AAAI), 2021. (CCF A)

IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning
Manli Zhang, Jianhong Zhang, Zhiwu Lu*, Tao Xiang, Mingyu Ding, and Songfang Huang
International Conference on Learning Representations (ICLR), 2021.

MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning
Nanyi Fei, Zhiwu Lu*, Tao Xiang, and Songfang Huang
International Conference on Learning Representations (ICLR), 2021.

HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers
Mingyu Ding, Xiaochen Lian, Linjie Yang, Peng Wang, Xiaojie Jin, Zhiwu Lu, and Ping Luo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (Oral, CCF A)

Counterfactual VQA: A Cause-Effect Look at Language Bias
Yulei Niu, Kaihua Tang, Hanwang Zhang, Zhiwu Lu, Xian-Sheng Hua, and Ji-Rong Wen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (CCF A)

L2M-GAN: Learning to Manipulate Latent Space Semantics for Facial Attribute Editing
Guoxing Yang, Nanyi Fei, Mingyu Ding, Guangzhen Liu, Zhiwu Lu*, and Tao Xiang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (Oral, CCF A)

Variational Context: Exploiting Visual and Textual Context for Grounding Referring Expressions
Yulei Niu, Hanwang Zhang, Zhiwu Lu, and Shih-Fu Chang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 43, no. 1, pp. 347-359, 2021. (CCF A)

Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning
Jiechao Guan, Zhiwu Lu*, Tao Xiang, Aoxue Li, An Zhao, and Ji-Rong Wen
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 43, no. 7, pp. 2510-2523, 2021. (CCF A)

2020
Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow
Mingyu Ding, Zhe Wang, Bolei Zhou, Jianping Shi, Zhiwu Lu*, and Ping Luo
AAAI Conference on Artificial Intelligence (AAAI), New York, USA, 2020. (CCF A)

Learning Depth-Guided Convolutions for Monocular 3D Object Detection
Mingyu Ding, Yuqi Huo, Hongwei Yi, Zhe Wang, Jianping Shi, Zhiwu Lu, and Ping Luo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, 2020. (CCF A)

Transferrable Feature and Projection Learning with Class Hierarchy for Zero-Shot Learning
Aoxue Li, Zhiwu Lu*, Jiechao Guan, Tao Xiang, Liwei Wang, and Ji-Rong Wen
International Journal of Computer Vision (IJCV), vol. 128, no. 12, pp. 2810-2827, 2020. (CCF A)

2019
Multi-Modal Multi-Scale Deep Learning for Large-Scale Image Annotation
Yulei Niu, Zhiwu Lu*, Ji-Rong Wen, Tao Xiang, and Shih-Fu Chang
IEEE Transactions on Image Processing (TIP), vol. 28, no. 4, pp. 1720-1731, 2019. (CCF A)

Coarse-to-Fine Grained Classification
Yuqi Huo, Yao Lu, Yulei Niu, Zhiwu Lu*, and Ji-Rong Wen
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, 2019. (CCF A)

Large-Scale Few-Shot Learning: Knowledge Transfer with Class Hierarchy,
Aoxue Li, Tiange Luo, Zhiwu Lu*, Tao Xiang, and Liwei Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019. (CCF A)

Recursive Visual Attention in Visual Dialog,
Yulei Niu, Hanwang Zhang, Manli Zhang, Jianhong Zhang, Zhiwu Lu*, and Ji-Rong Wen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019. (CCF A)

Face-Focused Cross-Stream Network for Deception Detection in Videos,
Mingyu Ding, An Zhao, Zhiwu Lu*, Tao Xiang, and Ji-Rong Wen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019. (CCF A)

2018
Domain-Invariant Projection Learning for Zero-Shot Recognition
An Zhao, Mingyu Ding, Jiechao Guan, Zhiwu Lu*, Tao Xiang, and Ji-Rong Wen
Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS), Montréal, Canada, 2018. (CCF A)

Large Scale Sparse Learning from Noisy Tags for Semantic Segmentation
Aoxue Li, Zhiwu Lu*, Liwei Wang, Peng Han, and Ji-Rong Wen
IEEE Transactions on Cybernetics (TCYB), vol. 48, no. 1, pp. 253-263, 2018. (ESI高被引论文)

2017
FeaBoost: Joint Feature and Label Refinement for Semantic Segmentation
Yulei Niu, Zhiwu Lu*, Songfang Huang, Xin Gao, and Ji-Rong Wen
AAAI Conference on Artificial Intelligence (AAAI), San Francisco, California, USA, 2017.

Zero-Shot Scene Classification for High Spatial Resolution Remote Sensing Images,
Aoxue Li, Zhiwu Lu*, Liwei Wang, Tao Xiang, and Ji-Rong Wen
IEEE Transactions on Geoscience and Remote Sensing (TGRS), vo. 55, no. 7, pp. 4157-4167, 2017.

Learning from Weak and Noisy Labels for Semantic Segmentation
Zhiwu Lu, Zhenyong Fu, Tao Xiang, Peng Han, Liwei Wang, and Xin Gao
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 39, no. 3, pp. 486-500, 2017. (CCF A)

2016
Large-Scale Sparse Clustering
Ruqi Zhang and Zhiwu Lu*
International Joint Conference on Artificial Intelligence (IJCAI), New York, USA, 2016.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction,
Xuefeng Cui, Zhiwu Lu, Sheng Wang, Jim Jing-Yan Wang, and Xin Gao
Bioinformatics, vol. 32, no. 12, pp. i332-i340, 2016.

2015
Social Image Parsing by Cross-Modal Data Refinement
Zhiwu Lu, Xin Gao, Songfang Huang, Liwei Wang, and Ji-Rong Wen
International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, 2015. (CCF A)

Social Image Parsing by Cross-Modal Data Refinement
Zhiwu Lu, Xin Gao, Songfang Huang, Liwei Wang, and Ji-Rong Wen
International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, 2015. (CCF A)

Noise-Robust Semi-Supervised Learning via Fast Sparse Coding
Zhiwu Lu and Liwei Wang
Pattern Recognition (PR), vol. 48, no. 2, pp. 605-612, 2015.

Learning Descriptive Visual Representation for Image Classification and Annotation,
Zhiwu Lu and Liwei Wang
Pattern Recognition (PR), vol. 48, no. 2, pp. 498-508, 2015.

Semantic Sparse Recoding of Visual Content for Image Applications
Zhiwu Lu, Peng Han, Liwei Wang, and Ji-Rong Wen
IEEE Transactions on Image Processing (TIP), vol. 24, no. 1, pp. 176-188, 2015. (CCF A)

2014
Direct Semantic Analysis for Social Image Classification
Zhiwu Lu, Liwei Wang, and Ji-Rong Wen
AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, 2014. (CCF A)

Spatial temporal pyramid matching using temporal sparse representation for human motion retrieval,
Liuyang Zhou, Zhiwu Lu, Howard Leung, and Lifeng Shang
The Visual Computer, vol. 30, no. 6-8, pp. 845-854, 2014. (Special Issue on CGI 2014, Best Paper Award)

2013
Unified Constraint Propagation on Multi-View Data
Zhiwu Lu and Yuxin Peng
AAAI Conference on Artificial Intelligence (AAAI), Bellevue, Washington, USA, 2013. (CCF A)

Learning Descriptive Visual Representation by Semantic Regularized Matrix Factorization
Zhiwu Lu and Yuxin Peng
International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013. (CCF A)

Latent Semantic Learning with Structured Sparse Representation for Human Action Recognition
Zhiwu Lu and Yuxin Peng
Pattern Recognition (PR), vol. 46, no. 7, pp. 1799-1809, 2013.

Exhaustive and Efficient Constraint Propagation: A Graph-Based Learning Approach and Its Applications,
Zhiwu Lu and Yuxin Peng
International Journal of Computer Vision (IJCV), vol. 103, no. 3, pp. 306-325, 2013. (CCF A)

荣誉奖励

  • 2021年设计首个公开的中文通用图文预训练模型BriVL
  • ICONIP 2018最佳学生论文奖亚军
  • 深度学习权威评测ImageNet 2015视频检测任务亚军
  • 2015年IBM SUR Award
  • IJCAI-15竞赛(Repeat Buyers Prediction)第4名
  • 中国人民大学2015届优秀学士学位论文指导老师
  • 计算机图形学国际会议CGI 2014最佳论文奖

社会兼职

  • Reviewer for IEEE TPAMI, IJCV, IEEE TIP, IEEE TMM, IEEE TNNLS, IEEE TKDE, TOIS
  • SPC/PC Member of ICML, NeurIPS, CVPR, ICCV, ECCV, AAAI, IJCAI, UAI
  • Member of CCF, ACM, IEEE

contact

电话:010-62515670

邮箱:luzhiwu(@)ruc.edu.cn

个人网页:https://sites.google.com/site/zhiwulu/

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