个人简介
杨文杰,男,硕士生导师,讲师
研究领域为多模态理解:表征对齐、多模融合;计算机视觉;模式识别: 特征选择、分类器设计;视觉监控应用:物体检测和检索关键技术;智能医疗:序列数据和医学图像分析、风险预估。
地址:bat365中文官方网站2号楼404
邮箱:hokkien.ywj@gmail.com
教育和工作经历
2023.05~至今 bat365官网登录入口bat365中文官方网站 讲师
2021.07~2023.04 北京快手科技 图像与视频处理算法研究员
2016.09~2021.07 中国科学院自动化研究所 博士
2012.09~2016.07 北京航空航天大学 学士
招生信息
学术硕士招生专业:计算机科学与技术
专业硕士招生专业:计算机技术、人工智能、软件工程
招生要求:感兴趣且好学。对以下研究内容感兴趣:面向电商商品和监控场景行人的大规模多模态学习(Large-Scale Multimodal Learning)、行人再识别(Person re-identification)、多标签分类(Multi-label classification)、面向糖尿病风险预估的序列数据和医学影像分析;主动学习研究领域知识、编程和英文等知识。
出版信息
[1] Wenjie Yang, H Huang, Z Zhang, X Chen, K Huang, S Zhang, "Towards rich feature discovery with class activation maps augmentation for person re-identification", The IEEE Conference on Computer Vision and Pattern Recognition, 2019. (CVPR, CCF-A)
[2] Wenjie Yang, Dangwei Li, Xiaotang Chen, Kaiqi Huang, "Bottom-up foreground-aware feature fusion for person search", Proceedings of the 28th ACM International Conference on Multimedia, 2020. (MM, CCF-A)
[3] Wenjie Yang, Houjing Huang, Xiaotang Chen, Kaiqi Huang, "Bottom-up foreground-aware feature fusion for practical person search", IEEE Transactions on Circuits and Systems for Video Technology, 2021. (TCSVT, SCI-II, IF8.4)
[4] Wenjie Yang, Yiyi Chen, Yan Li, Yanhua Cheng, Xudong Liu, Quan Chen, Han Li, "Cross-view Semantic Alignment for Livestreaming Product Recognition", IEEE International Conference on Computer Vision, 2023. (ICCV, CCF-A)
[5] Xuehan Bai, Yan Li, Yanhua Cheng, Wenjie Yang, Quan Chen, Han Li, "Cross-Domain Product Representation Learning for Rich-Content E-Commerce", IEEE International Conference on Computer Vision, 2023. (ICCV, CCF-A, Corresponding author)
[6] Houjing Huang, Wenjie Yang, Jinbin Lin, Guan Huang, Jiamiao Xu, Guoli Wang, Xiaotang Chen, Kaiqi Huang, "Improve person re-identification with part awareness learning", IEEE Transactions on Image Processing, 2020. (TIP, SCI-I, IF10.6)
[7] 杨文杰,“基于多模态理解的快手电商 SPU 体系智能化构建”, CN114266921A, 2022.04.01. (发明专利)
[8] 杨文杰,程衍华,“基于 Transformer 的细粒度多模态商品特征表达”, CN116229202A, 2023.06.06. (发明专利)