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檀振山
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Education and Working Experiences

    Education:

l  Ph.D, Fudan University, 2023

l  M.S, Wuhan University, 2019

l  B.S, Wuhan University, 2016

     Working Experiences:

l  2013 – Present:  Nanjing University of Information Science & Technology


Professional Activities

           Reviewer of CVPR, ICCV, TCSVT, NeuNet, KBS, et al.


Research Interests

          1) Computer Vision: Object Detection, Segmentation, Remote Sensing Image Processing, Color/Style Transfer, Image Inpainting, etc.

            2) Artificial Intelligence Security: Image/Video Manipulation Detection and Localization, Steganography, Adversarial Machine Learning, etc.


Selected papers from 2019

17. Learn More and Learn Usefully: Truncation Compensation Network for Semantic Segmentation of High-Resolution Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing, 2024.

16. Co-saliency detection with two-stage co-attention mining and individual calibration. Engineering Applications of Artificial Intelligence, 2023.

15. Triplet Spatiotemporal Aggregation Network for Video Saliency Detection. IEEE International Conference on Multimedia and Expo (oral), 2023.

14. Bridging feature complementarity gap between encoder and decoder for salient object detection. Digital Signal Processing, 2023.

13. Dual-Discriminator Generative Adversarial Network with Uniform Color Information Extraction for Color Constancy. Journal of Imaging Science and Technology, 2023.

12. A Unified Video Semantics Extraction and Noise Object Suppression Network for Video Saliency Detection. International Conference on Artificial Neural Networks, 2023.

11. UTC: a unified transformer with inter-task contrastive learning for visual dialog. IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022.

10. Semantic Pre-alignment and Ranking Learning with Unified Framework for Cross-modal Retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 2022.

9. Co-saliency detection with intra-group two-stage group semantics propagation and inter-group contrastive learning. Knowledge-Based Systems, 2022.

8. A Unified Two-Stage Group Semantics Propagation and Contrastive Learning Network for Co-Saliency Detection. IEEE International Conference on Multimedia and Expo (oral), 2022.

7. Visual context learning based on textual knowledge for image–text retrieval. Neural Networks, 2022.

6. A Unified Multiple Inducible Co-Attentions and Edge Guidance Network for Co-Saliency Detection. International Conference on Artificial Neural Networks, 2022.

5. Feature Recalibration Network for Salient Object Detection. International Conference on Artificial Neural Networks, 2022.

4. Depth scale balance saliency detection with connective feature pyramid and edge guidance. Applied Intelligence, 2021.

3. SBN: Scale Balance Network for Accurate Salient Object Detection. International Joint Conference on Neural Networks, 2020.

2. Salient object detection with edge recalibration. International Conference on Artificial Neural Networks, 2020.

1. Directive local color transfer based on dynamic look-up table. Signal Processing: Image Communication, 2019.


  • Education Background
  • Work Experience
  • 复旦大学
  • Doctoral Degree in Science

  • 武汉大学
  • Master's Degree in Engineering

  • 武汉大学
  • Bachelor's Degree in Engineering

  • Social Affiliations
  • Research Focus
  • 中国图象图形学学会数字媒体取证与安全专业委员会委员

  • 中国仪器仪表学会图像科学与工程专业委员会委员

  • 江苏省计算机学会信息安全专业委员会委员

  • CVPR、ICCV、TGRS、TMM、TCSVT等多个国际会议期刊的审稿人

Personal Information


Gender : Male

Alma Mater : 复旦大学

Education Level : With Certificate of Graduation for Doctorate Study

Degree : Doctoral Degree in Science

Status : 在岗

School/Department : 计算机学院、网络空间安全学院(数字取证教育部工程研究中心、公共计算机教学部)

Contact Information : zstan@nuist.edu.cn

PostalAddress : 临江楼1506

Email : zstan@nuist.edu.cn

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