Zhu Chao
朱超,博士,副教授,项目博士生导师,分别于2005、2008和2012年在西安电子科技大学、西安交通大学和法国里昂中央理工大学获得学士、硕士和博士学位;于2013年在北京大学计算机科学技术研究所从事博士后研究工作;于2016年加入北京科技大学计算机与通信工程学院工作。长期从事计算机视觉与模式识别方面的研究,重点研究针对图像和视频内容理解、以人为中心的视觉任务等相关理论与关键技术,在特征提取、图像/视频分类、目标检测与识别等方面取得了多项创新成果;近年来也结合学校的行业特色,开展钢铁工业智能方面的研究与应用。目前已发表学术论文40余篇,其中以第一、通讯作者在IEEE TIP、Pattern Recognition、IEEE TITS、Neurocomputing等国际权威期刊和CVPR、AAAI、ACM Multimedia、ICME、ICMR、ICPR等国际顶级与主流会议上发表论文20余篇(包括CCF-A类/SCI一区论文近10篇);论文在谷歌学术中引用总计近千次,其中一作Pattern Recognition论文在Web of Science中单篇他引超100次。主持国家自然科学基金(面上2项、青年1项)、科技创新2030—“新一代人工智能”重大项目子课题1项、北京市自然科学基金(青年1项)、中央高校基础科研基金和中国博士后科学基金(面上)等多项国家级/省部级科研项目,主持中兴通讯等企业合作项目2项,并参与国家重点研发计划、863计划、腾讯企业合作、法国国家研究署和欧盟研究基金等多个项目。已授权发明专利1项,受理10余项。作为主要成员参加了多项计算机视觉与模式识别领域的国际国内算法评测竞赛并取得了较好成绩,包括在2011年国际计算机视觉算法评测Pascal VOC Challenge的图像分类竞赛中获得全球第五;在2012年国际图像评测ImageCLEF Photo Annotation的图像标注竞赛中获得国际第一。
期刊论文:
1. C. Zhu and Y. Peng, “A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling”, IEEE Transactions on Image Processing (T-IP), 2015, Vol.24, No.12, pp.5619-5629. (SCI 1区,CCF-A类)
2. C. Zhu, C.-E. Bichot and L. Chen, “Image Region Description Using Orthogonal Combination of Local Binary Patterns Enhanced with Color Information”, Pattern Recognition (PR), 2013, Vol.46, No.7, pp.1949-1963. (SCI 1区,CCF-B类)
3. Y. Ma, M. Liu, C. Zhu* and X.-C. Yin, “HA-FGOVD: Highlighting Fine-Grained Attributes via Explicit Linear Composition for Open-Vocabulary Object Detection”, IEEE Transactions on Multimedia (T-MM), 2025, Vol.27, pp. 3171-3183. (SCI 1区,CCF-B类)
4. Y. He, C. Zhu* and X.-C. Yin, “Occluded Pedestrian Detection via Distribution-Based Mutual-Supervised Feature Learning”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022, Vol.23, No.8, pp. 10514-10529. (SCI 1区,CCF-B类)
5. D. Huang, C. Zhu, Y. Wang and L. Chen, “HSOG: A Novel Local Image Descriptor Based on Histograms of the Second-Order Gradients”, IEEE Transactions on Image Processing (T-IP), 2014, Vol. 23, No. 11, pp.4680-4695. (SCI 1区,CCF-A类)
6. C. Zhu and Y. Peng, “Discriminative Latent Semantic Feature Learning for Pedestrian Detection”, Neurocomputing, 2017, Vol.238, pp.126-138. (SCI 2区,CCF-C类)
会议论文:
1. C. Zhu and Y. Peng, “Group Cost-Sensitive Boosting for Multi-Resolution Pedestrian Detection”, in Proc. of 30th AAAI Conference on Artificial Intelligence (AAAI), 2016, pp.3676-3682. (CCF-A类, oral)
2. C. Zhu and Y. Peng, “A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling”, in Proc. of 29th AAAI Conference on Artificial Intelligence (AAAI), 2015, pp.3878-3884. (CCF-A类, oral)
3. M. Liu, C. Zhu*, et al, “Unsupervised Multi-view Pedestrian Detection”, in Proc. of 32nd ACM International Conference on Multimedia (ACM MM), 2024, pp. 1034-1042. (CCF-A类)
4. M. Liu, J. Jiang, C. Zhu* and X.-C. Yin, “VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision”, in Proc. of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp.6662-6671. (CCF-A类)
5. H. Gao, C. Zhu*, et al, “CAliC: Accurate and Efficient Image-Text Retrieval via Contrastive Alignment and Visual Contexts Modeling”, in Proc. of 30th ACM International Conference on Multimedia (ACM MM), 2022, pp. 4957-4966. (CCF-A类)
6. M. Liu, C. Zhu*, J. Wang and X.-C. Yin, “Adaptive Pattern-Parameter Matching for Robust Pedestrian Detection”, in Proc. of 35th AAAI Conference on Artificial Intelligence (AAAI), 2021, pp.2154-2162. (CCF-A类)
7. C. Zhu, C.-E. Bichot and L. Chen, “Visual Object Recognition Using DAISY Descriptor”, in Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2011, pp.1-6. (CCF-B类)
8. S. Ren, C. Zhu*, M. Liu and X.-C. Yin, “Towards Discriminative Semantic Relationship for Fine-grained Crowd Counting”, in Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2023, pp.84-89. (CCF-B类)
9. D. Huang, C. Zhu, C.-E. Bichot, Y. Wang and L. Chen, “HSOG: A Novel Local Descriptor based on Histograms of Second Order Gradients for Object Categorization”, in Proc. of ACM International Conference on Multimedia Retrieval (ICMR), 2013, pp.199-206. (CCF-B类)
10. C. Zhu, C.-E. Bichot and L. Chen, “Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition”, in Proc. of 20th IAPR International Conference on Pattern Recognition (ICPR), 2010, pp.3065-3068. (CCF-C类)
11. T. Liu, C. Zhu* and L. Yang, “Efficient Text-Based Person Search Via Single-Stage Identity-Guided Attribute Parsing and Alignment”, in Proc. of 26th IAPR International Conference on Pattern Recognition (ICPR), 2022, pp.4111-4117. (CCF-C类)
12. Y. He, C. Zhu* and X.-C. Yin, “Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection”, in Proc. of 25th IAPR International Conference on Pattern Recognition (ICPR), 2020, pp.8453-8460. (CCF-C类, oral)
13. X. Li, C. Yang, S.-L. Chen, C. Zhu* and X.-C. Yin, “Semantic Bilinear Pooling for Fine-Grained Recognition”, in Proc. of 25th IAPR International Conference on Pattern Recognition (ICPR), 2020, pp.3660-3666. (CCF-C类)
14. Y. Wang, C. Zhu* and X.-C. Yin, “A Hybrid Self-Attention Model for Pedestrians Detection”, in Proc. of 27th International Conference on Neural Information Processing (ICONIP), 2020, pp.62-74. (CCF-C类)
纵向项目:
1. 基于生成式模型的开放类别与无监督目标检测关键技术研究,国家自然科学基金面上项目,负责人,2025.01-2028.12
2. 钢铁智能制造过程中数据认知与生产决策技术及应用,科技创新2030——新一代人工智能重大项目,子课题负责人,2023.03-2027.02
3. 面向小尺度与遮挡处理的目标检测关键技术研究,国家自然科学基金面上项目,负责人,2021.01-2024.12
4. 基于视觉注意力建模与深度特征金字塔网络的目标检测研究,国家自然科学基金青年项目,负责人,2018.01-2020.12
5. 基于深度网络中子类别感知和上下文增强的目标检测研究,北京市自然科学基金青年项目,负责人,2017.01-2018.12
6. 适用于目标检测的多尺度特征增强深度神经网络研究,中央高校基础科研资助项目,负责人,2017.01-2018.12
7. 基于隐含语义表示和自适应子类建模的目标检测研究,中国博士后科学基金面上项目,负责人,2014.05-2015.12
横向项目:
1. 行业多模态时序预测大模型,负责人,2025.07-2026.12
2. 典型场景目标检测与识别研究,负责人,2022.06-2023.03
3. 多模态视频广告理解技术,腾讯(深圳),参与人,2020.09-2021.09
4. 面向广告场景图片的文本识别技术,腾讯(深圳),参与人,2017.12-2019.12
5. 网络场景图片文字检测与识别研究,腾讯(深圳),参与人,2016.12-2017.12
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