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陈添水
Tianshui Chen
Research Scientist
tianshuichen@gmail.com

教师简介


He is currently an associate research director at DMAI Co., Ltd. Before that, he obtained PHD. degree at Human Cyber Physical Intelligence Integration Lab of Sun Yat-Sen University advised by Prof. Liang Lin. He received my Bachelor Degree from Sun Yat-sen University in 2013. He also worked as a research assistant (2016.06-2017.06) in The Hong Kong Polytechnic University under the guidance of Prof. Lei Zhang.

 

 

研究领域


Computer Vision

  • - General/fine-Grained image classification

  • - Social relationship classification

  • - Object proposal generation

  • - Salient object detection

Machine Learning

  • - Deep learning

  • - Deep reinforcement learning

  • - Knowledge representation learning

Robotics

  • - Robotics perception

  • - Task planning

 

 

获奖及荣誉


Professional Awards:

  • - Aug 2018 – Present , Rank first at Pascal VOC 2012 leaderboard July 2017
  • - World's FIRST 10K Best Paper Award Diamond Award in ICME 2017 Nov. 2015
  • - The Eleventh Place, Large Scale Visual Recognition Challenge (ILSVRC) 2015, Det Task
  • - Aug. 2014, The Third Place, Large Scale Visual Recognition Challenge (ILSVRC) 2014, CLS-LOC Task

Student Awards:

  • - Oct 2017, National Scholarship
  • - Oct 2014, SYSU Outstanding Graduate Student
  • - 2013 – 2018, SYSU Outstanding Ph.D. Student Fellowship
  • - June 2013, SYSU Outstanding Graduates
  • - Nov. 2011, National Encouragement Scholarship
  • - 2009 – 2012, The Second, Second, Third Prizes Scholarship

 

教育背景


Aug. 2013 – Dec. 2018, Ph.D., Computer Science and Technology, Sun Yat-Sen University

Sep. 2009 – June 2013, B.S., Electronic Information Science and Technology, Sun YatSen University

 

工作经历


Dec. 2018 – Present, Principal Researcher, DMAI Research

June 2016 – June 2017, Research Assistant, The Hong Kong Polytechnic University

 

主要学术兼职


Reviewers for the Following Conferences and Journals:

  • - International Conference on Computer Vision and Pattern Recognition (CVPR) 2019/2020
  • - IEEE International Conference on Computer Vision (ICCV) 2019
  • - AAAI Conference on Artificial Intelligence (AAAI) 2020
  • - Transactions on Neural Networks and Learning Systems (T-NNLS)
  • - IEEE Transactions on Image Processing (TIP)
  • - IEEE Transactions on Multimedia (TMM)
  • - Pattern Recognition (PR)
  • - Neurocomputating

 

代表性论著


Chao Chen, Guanbin Li, Ruijia Xu, Tianshui Chen, Meng Wang & Liang Lin. (2019). Clusternet: Deep hierarchical cluster network with rigorously rotation-invariant representation for point cloud analysis. In Proc. of international conference on computer vision and pattern recognition (CVPR).

Jie Wu, Tianshui Chen, Hefeng Wu, Qing Wang, Zhi Yang & Liang Lin. (2019). Concrete image captioning by integrating content sensitive and global discriminative objective. In Proc. of ieee international conference on multimedia and expo (ICME).

Pengxiang Yan, Guanbin Li, Yuan Xie, Tianshui Chen, Zhen Li & Liang Lin. (2019). Semi-supervised video salient object detection using pseudo-labels. In Proc. of international conference on computer vision (ICCV).

Tianshui Chen, Muxin Xu, Xiaolu Hui, Hefeng Wu & Liang Lin. (2019). Learning semantic-specific graph representation for multi-label image recognition. In Proc. of international conference on computer vision (ICCV).

Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu & Liang Lin. (2019). Neural task planning with and-or graph representations. IEEE Transactions on Mutimedia (TMM).

Tianshui Chen, Weihao Yu, Riquan Chen & Liang Lin. (2019). Knowledge-embedded routing network for scene graph generation. In Proc. of international conference on computer vision and pattern recognition (CVPR).

Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu & Xiaonan Luo. (2018). Knowledge-embedded representation learning for fine-grained image recognition. In Proc. of international joint conference on artificial intelligence (IJCAI).

Tianshui Chen, Liang Lin, Wangmeng Zuo, Xiaonan Luo & Lei Zhang. (2018). Learning a wavelet-like auto-encoder to accelerate deep neural networks. In Proc. of aaai conference on artificial intelligence (AAAI).

Tianshui Chen, Lin, Liang, Xian Wu, Nong Xiao & Xiaonan Luo. (2018). Learning to segment object candidates via recursive neural networks. IEEE Transactions on Image Processing (TIP).

Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo & Liang Lin. (2018). Fine-grained representation learning and recognition by exploiting hierarchical semantic embedding. In Proc. of acm international conference on multimedia (ACM MM).

Tianshui Chen, Zhouxia Zhou, Guanbin Li & Liang Lin. (2018). Recurrent attentional reinforcement learning for multi-label image recognition. In Proc. of aaai conference on artificial intelligence (AAAI).

Zhouxia Wang, Tianshui Chen, Jimmy Ren, Weihao Yu, Hui Cheng & Liang Lin. (2018). Deep reasoning with knowledge graph for social relationship understanding. In Proc. of international joint conference on artificial intelligence (IJCAI).

Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan & Ebroul Izquierdo. (2017). Content-adaptive sketch portrait generation by decompositional representation learning. IEEE Transactions on Image Processing (TIP).

Liang Lin, Lili Huang, Tianshui Chen, Yukang Gan & Hui Cheng. (2017). Knowledge-guided recurrent neural network learning for task-oriented action prediction. In Ieee international conference on multimedia and expo (ICME).

Zhouxia Wang, Tianshui Chen, Guanbin Li, Ruijia Xu & Liang Lin. (2017). Multi-label image recognition by recurrently discovering attentional regions. In Proc. of ieee international conference on computer vision (ICCV).

Shuye Zhang, Mude Lin, Tianshui Chen, Lianwen Jin & Liang Lin. (2016). Character proposal network for robust text extraction. In Proc. of ieee international conference on acoustics, speech and signal processing (ICASSP).

Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo & Xuelong Li. (2016). Disc: Deep image saliency computing via progressive representation learning. IEEE Transactions on Neural Network and Learning System (TNNLS).

 

 

Tianshui Chen
Tianshui Chen
Research Scientist
tianshuichen@gmail.com

教师简介


He is currently an associate research director at DMAI Co., Ltd. Before that, he obtained PHD. degree at Human Cyber Physical Intelligence Integration Lab of Sun Yat-Sen University advised by Prof. Liang Lin. He received my Bachelor Degree from Sun Yat-sen University in 2013. He also worked as a research assistant (2016.06-2017.06) in The Hong Kong Polytechnic University under the guidance of Prof. Lei Zhang.

 

 

研究领域


Computer Vision

  • - General/fine-Grained image classification

  • - Social relationship classification

  • - Object proposal generation

  • - Salient object detection

Machine Learning

  • - Deep learning

  • - Deep reinforcement learning

  • - Knowledge representation learning

Robotics

  • - Robotics perception

  • - Task planning

 

 

获奖及荣誉


Professional Awards:

  • - Aug 2018 – Present , Rank first at Pascal VOC 2012 leaderboard July 2017
  • - World's FIRST 10K Best Paper Award Diamond Award in ICME 2017 Nov. 2015
  • - The Eleventh Place, Large Scale Visual Recognition Challenge (ILSVRC) 2015, Det Task
  • - Aug. 2014, The Third Place, Large Scale Visual Recognition Challenge (ILSVRC) 2014, CLS-LOC Task

Student Awards:

  • - Oct 2017, National Scholarship
  • - Oct 2014, SYSU Outstanding Graduate Student
  • - 2013 – 2018, SYSU Outstanding Ph.D. Student Fellowship
  • - June 2013, SYSU Outstanding Graduates
  • - Nov. 2011, National Encouragement Scholarship
  • - 2009 – 2012, The Second, Second, Third Prizes Scholarship

 

教育背景


Aug. 2013 – Dec. 2018, Ph.D., Computer Science and Technology, Sun Yat-Sen University

Sep. 2009 – June 2013, B.S., Electronic Information Science and Technology, Sun YatSen University

 

工作经历


Dec. 2018 – Present, Principal Researcher, DMAI Research

June 2016 – June 2017, Research Assistant, The Hong Kong Polytechnic University

 

主要学术兼职


Reviewers for the Following Conferences and Journals:

  • - International Conference on Computer Vision and Pattern Recognition (CVPR) 2019/2020
  • - IEEE International Conference on Computer Vision (ICCV) 2019
  • - AAAI Conference on Artificial Intelligence (AAAI) 2020
  • - Transactions on Neural Networks and Learning Systems (T-NNLS)
  • - IEEE Transactions on Image Processing (TIP)
  • - IEEE Transactions on Multimedia (TMM)
  • - Pattern Recognition (PR)
  • - Neurocomputating

 

代表性论著


Chao Chen, Guanbin Li, Ruijia Xu, Tianshui Chen, Meng Wang & Liang Lin. (2019). Clusternet: Deep hierarchical cluster network with rigorously rotation-invariant representation for point cloud analysis. In Proc. of international conference on computer vision and pattern recognition (CVPR).

Jie Wu, Tianshui Chen, Hefeng Wu, Qing Wang, Zhi Yang & Liang Lin. (2019). Concrete image captioning by integrating content sensitive and global discriminative objective. In Proc. of ieee international conference on multimedia and expo (ICME).

Pengxiang Yan, Guanbin Li, Yuan Xie, Tianshui Chen, Zhen Li & Liang Lin. (2019). Semi-supervised video salient object detection using pseudo-labels. In Proc. of international conference on computer vision (ICCV).

Tianshui Chen, Muxin Xu, Xiaolu Hui, Hefeng Wu & Liang Lin. (2019). Learning semantic-specific graph representation for multi-label image recognition. In Proc. of international conference on computer vision (ICCV).

Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu & Liang Lin. (2019). Neural task planning with and-or graph representations. IEEE Transactions on Mutimedia (TMM).

Tianshui Chen, Weihao Yu, Riquan Chen & Liang Lin. (2019). Knowledge-embedded routing network for scene graph generation. In Proc. of international conference on computer vision and pattern recognition (CVPR).

Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu & Xiaonan Luo. (2018). Knowledge-embedded representation learning for fine-grained image recognition. In Proc. of international joint conference on artificial intelligence (IJCAI).

Tianshui Chen, Liang Lin, Wangmeng Zuo, Xiaonan Luo & Lei Zhang. (2018). Learning a wavelet-like auto-encoder to accelerate deep neural networks. In Proc. of aaai conference on artificial intelligence (AAAI).

Tianshui Chen, Lin, Liang, Xian Wu, Nong Xiao & Xiaonan Luo. (2018). Learning to segment object candidates via recursive neural networks. IEEE Transactions on Image Processing (TIP).

Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo & Liang Lin. (2018). Fine-grained representation learning and recognition by exploiting hierarchical semantic embedding. In Proc. of acm international conference on multimedia (ACM MM).

Tianshui Chen, Zhouxia Zhou, Guanbin Li & Liang Lin. (2018). Recurrent attentional reinforcement learning for multi-label image recognition. In Proc. of aaai conference on artificial intelligence (AAAI).

Zhouxia Wang, Tianshui Chen, Jimmy Ren, Weihao Yu, Hui Cheng & Liang Lin. (2018). Deep reasoning with knowledge graph for social relationship understanding. In Proc. of international joint conference on artificial intelligence (IJCAI).

Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan & Ebroul Izquierdo. (2017). Content-adaptive sketch portrait generation by decompositional representation learning. IEEE Transactions on Image Processing (TIP).

Liang Lin, Lili Huang, Tianshui Chen, Yukang Gan & Hui Cheng. (2017). Knowledge-guided recurrent neural network learning for task-oriented action prediction. In Ieee international conference on multimedia and expo (ICME).

Zhouxia Wang, Tianshui Chen, Guanbin Li, Ruijia Xu & Liang Lin. (2017). Multi-label image recognition by recurrently discovering attentional regions. In Proc. of ieee international conference on computer vision (ICCV).

Shuye Zhang, Mude Lin, Tianshui Chen, Lianwen Jin & Liang Lin. (2016). Character proposal network for robust text extraction. In Proc. of ieee international conference on acoustics, speech and signal processing (ICASSP).

Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo & Xuelong Li. (2016). Disc: Deep image saliency computing via progressive representation learning. IEEE Transactions on Neural Network and Learning System (TNNLS).