个人简述：
陈添水，广东工业大学“青年百人计划”副教授。研究方向主要是人工智能、视觉计算、生成式AI，在人工智能领域顶级期刊和会议（TPAMI/TIP/TNNLS/TMM/CVPR/ICCV/AAAI等）发表论文40余篇，其中包括第一作者TPAMI（人工智能领域最顶级期刊之一）论文2篇、ICME 2017获得最佳论文钻石奖、多篇论文入选ESI高被引。相关工作受到业内广泛关注，谷歌引用1900+，H-index 19。申请和授权多项发明专利。主持国家自然科学基金青年项目、广州科技大脑基础与应用基础项目。
教育背景：
[1] 2013.08-2018.12 博士 计算机科学与技术 中山大学
[2] 2009.09-2013.06 学士 电子信息科学与技术专业 中山大学
工作经历：
[1] 2021.12-至今 副教授 信息工程学院 广东工业大学
[2] 2019.01-2021.11 研究总监 暗物智能科技（广州）有限公司
[3] 2016.06-2017.06 助理研究员 香港理工大学
学术兼职：
[1] 担任TPAMI、IJCV、TIP、TNNLS、TMM等人工智能顶级期刊审稿人
[2] 担任ICLR、CVPR、ICCV、AAAI、IJCAI等人工智能顶级会议审稿人
主要论文：
代表性期刊论文：
[1] Tianshui Chen, Tao Pu, Yuan Xie, Hefeng Wu, Lingbo Liu, and Liang Lin. Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 1371 – 1384, 44(3), 2022. (中科院一区, CCF A类, ESI高被引)
[2] Tianshui Chen, Liang Lin, Xiaolu Hui, Riquan Chen, Hefeng Wu. Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 44(12), 9887 – 9903, 2022. (中科院一区, CCF A类, ESI高被引)
[3] Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu, and Liang Lin. Neural Task Planning with And-Or Graph Representations. IEEE Transactions on Multimedia (T-MM), 21(4), 1022-1034, 2019. (中科院一区, CCF B类)
[4] Tianshui Chen, Liang Lin, Xian Wu, Nong Xiao, and Xiaonan Luo. Learning to Segment Object Candidates via Recursive Neural Networks. IEEE Transactions on Image Processing (T-IP), 27(12), 5827-5839, 2018. (中科院一区, CCF A类)
[5] Tianshui Chen, Liang Lin, Lingbo Liu, Xiao-nan Luo, and Xuelong Li. DISC: Deep Image Saliency Computing via Progressive Representation Learning. IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 27(6): 1135-1149, 2016. (中科院一区, CCF B类)
[6] Jie Wu, Tianshui Chen*, Hefeng Wu, Zhi Yang, Guangchun Luo, and Liang Lin. Fine Grained Image Captioning with Global-Local Discriminative Objective. IEEE Transactions on Multimedia (T-MM), 2020. (中科院一区, CCF B类)
[7] Zhijing Yang, Junyang Chen, Yukai Shi, Hao Li, Tianshui Chen, Liang Lin. OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup. IEEE Transactions on Multimedia (T-MM), 2023. (中科院一区, CCF B类)
[8] Lingbo Liu, Zewei Yang, Guanbin Li, Kuo Wang, Tianshui Chen, and Liang Lin. Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction. IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2022. (中科院一区, CCF B类)
[9] Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan, and Ebroul Izquierdo. Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning. IEEE Trans-actions on Image Processing (T-IP), 26(1): 328-339, 2017. (中科院一区, CCF A类)
代表性会议论文：
[10] Tianshui Chen, Tao Pu, Yuan Xie, Hefeng Wu, and Liang Lin. Structured Semantic Transfer for Multi-Label Recognition with Partial Labels. Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF A类)
[11] Tianshui Chen, Muxin Xu, Xiaolu Hui, Hefeng Wu, Liang Lin. Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition. Proc. of IEEE International Conference on Computer Vision (ICCV), 2019. (CCF A类).
[12] Tianshui Chen, Weihao Yu, Riquan Chen, Liang Lin. Knowledge-Embedded Routing Network for Scene Graph Generation. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A类).
[13] Tianshui Chen, Liang Lin, Wangmeng Zuo, Xiaonan Luo, and Lei Zhang. Learning a Wavelet-like Auto-Encoder to Accelerate Deep Neural Networks. Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2018. (CCF A类, oral)
[14] Tianshui Chen, Zhouxia Wang, Guanbin Li, and Liang Lin. Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition. Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2018. (CCF A类)
[15] Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu, Xiaonan Luo. Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition. Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. (CCF A类, oral)
[16] Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo, Liang Lin. Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding. Proc. of ACM International Conference on Multimedia (ACM MM), 2018. (CCF A类, oral)
[17] Yuan Xie, Tianshui Chen*, Tao Pu, Hefeng Wu, Liang Lin. Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition. Proc. of ACM International Conference on Multimedia (ACM MM), 2020. (CCF A类, oral)
[18] Jie Wu, Tianshui Chen*, Lishan Huang, Hefeng Wu, Guanbin Li, Ling Tian, Liang Lin. Active Object Search. Proc. of ACM International Conference on Multimedia (ACM MM), 2020. (CCF A类, oral)
[19] Tao Pu#, Tianshui Chen#, Hefeng Wu, and Liang Lin. Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels. Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF A类)
[20] Zhouxia Wang#, Tianshui Chen#, Jimmy Ren, Weihao Yu, Hui Cheng, Liang Lin. Deep Reasoning with Knowledge Graph for Social Relationship Understanding. Proc. of International Joint Conference on Artificial Intelligence (IJCAI), 2018. (CCF A类, oral)
[21] Zhouxia Wang#, Tianshui Chen#, Guanbin Li, Ruijia Xu, and Liang Lin. Multi-label Image Recognition by Recurrently Discovering Attentional Regions. Proc. of IEEE International Conference on Computer Vision (ICCV), 2017. (CCF A类)
[22] Riquan Chen#, Tianshui Chen#, Xiaolu Hui, Hefen Wu, Guanbin Li, and Liang Lin. Knowledge Graph Transfer Network for Few-Shot Recognition. Proc. of AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF A类, oral)
[23] Zhenghua Peng, Yu Luo, Tianshui Chen, Keke Xu, Shuangping Huang. Perception and Semantic Aware Regularization for Sequential Confidence Calibration. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. (CCF A类)
[24] Yupei Lin, Sen Zhang, Tianshui Chen, Yongyi Lu, Guangping Li, Yukai Shi. Exploring negatives in contrastive learning for unpaired image-to-image translation. Proc. of ACM International Conference on Multimedia (ACM MM), 2022. (CCF A类, oral)
[25] Lingbo Liu, Jiaqi Chen, Hefeng Wu, Tianshui Chen, Guanbin Li, Liang Lin. Efficient Crowd Counting via Structured Knowledge Transfer. Proc. of ACM International Conference on Multimedia (ACM MM), 2020. (CCF A类)
[26] Pengxiang Yan, Guanbin Li, Yuan Xie, Zhen Li, Chuan Wang, Tianshui Chen, Liang Lin. Semi-Supervised Video Salient Object Detection Using Pseudo-Labels. Proc. of IEEE Inter-national Conference on Computer Vision (ICCV), 2019. (CCF A类)
[27] Chao Chen, Guanbin Li, Ruijia Xu, Tianshui Chen, Meng Wang, Liang Lin. ClusterNet: Deep Hierarchical Cluster Network with Rigorously Rotation-Invariant Representation for Point Cloud Analysis. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.(CCF A类)
科研项目：
1. 国家自然科学基金委员会, 青年科学基金项目，62206060，融合知识表达学习的少标注样本视觉理解关键技术研究，2023-01-01至2025-12-31，在研，主持
教学活动：
《人工智能导论》
学生要求：
研究生：具有一定编程基础，致力于人工智能相关方向研究，毕业后有意愿继续攻读博士或出国深造者优先考虑，可协助推荐
本科生：具有一定编程基础，致力于人工智能相关方向研究，有意在本校读研优先
