Guanchun Wang

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Ph.D Candidate
School of Artificial Intelligence, Xidian University
Email: gwang_2@stu.xidian.edu.cn
[Google Scholar] [ResearchGate] [ORCID]

Short Bio

I am a fourth-year Ph.D. student at Xidian University (XDU), supervised by Prof. Xiangrong Zhang. My research interests include weakly supervised learning, object detection, and remote sensing image analysis.

Recently, I'm working on weakly supervised object detection (WSOD), weakly supervised semantic segmentation (WSSS), remote sensing object detection (RSOD), and hyperspectral image change detection (HICD).

Education

News

  • [2024.04] One paper is accepted by TNNLS.
  • [2024.01] One collaborative paper is accepted by TGRS.
  • [2023.09] One collaborative paper is accepted by GRSM.
  • [2023.08] One collaborative paper is accepted by TGRS.
  • [2023.07] One collaborative paper is accepted by ICCV.
  • [2023.06] One paper is accepted by TGRS.
  • [2023.05] One collaborative paper is accepted by TGRS.
  • [2023.04] One collaborative paper is accepted by IGARSS.
  • [2023.01] One paper is accepted by ISPRS.
  • [2022.07] One paper is accepted by IJCAI.
  • [2020.09] One paper is accepted by TGRS.
  • [2020.09] One collaborative paper is accepted by IGARSS.

    • Publications

  • [1] G. Wang, X. Zhang, Z. Peng, X. Jia, X. Tang, L. Jiao, “MOL: Towards accurate weakly supervised remote sensing object detection via Multi-view nOisy Learning”, ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS), (SCI Q1 Top, IF=12.7).

  • [2] G. Wang, X. Zhang, Z. Peng, X. Tang, H. Zhou, L. Jiao, “Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information”, International Joint Conference on Artificial Intelligence (IJCAI), (CCF A).

  • [3] G. Wang, X. Zhang, Z. Peng, T. Zhang, X. Tang, H. Zhou, L. Jiao, “Negative Deterministic Information based Multiple Instance Learning for Weakly Supervised Object Detection and Segmentation”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (SCI Q1 Top, IF=10.4).

  • [4] G. Wang, X. Zhang, P. Zhu, X. Tang, P. Chen, L. Jiao, H. Zhou, “High-Quality Angle Prediction for Oriented Object Detection in Remote Sensing Images”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2).

  • [5] X. Zhang, G. Wang, P. Zhu, T. Zhang, C. Li, L. Jiao, “GRS-Det: An anchor-free rotation ship detector based on Gaussian-mask in remote sensing images”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2).

  • [6] Z. Peng, G. Wang, L. Xie, D. Jiang, W. Shen, Q. Tian, “USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation”, International Conference on Computer Vision (ICCV), (CCF A).

  • [7] X. Zhang, T. Zhang, G. Wang, P. Zhu, X. Tang, X. Jia, L. Jiao, “Remote Sensing Object Detection Meets Deep Learning: A Meta-review of Challenges and Advances”, IEEE Geoscience and Remote Sensing Magazine (GRSM), (SCI Q1 Top, IF=14.6).

  • [8] X. Zhang, S. Tian, G. Wang, X. Tang, J. Feng, L. Jiao, “CAST: A CAscade Spectral aware Transformer for Hyperspectral Image Change Detection”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2).

  • [9] X. Zhang, X. Fan, G. Wang, P. Chen, X. Tang, L. Jiao, “MFGNet: Multi-branch Feature Generation Networks for Few-Shot Remote Sensing Scene Classification”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2).

  • [10] S. Tian, X. Zhang, G. Wang, X. Han, P. Chen, X. Cheng, “CTACL: Hyperspectral Image Change Detection based on Adaptive Contrastive Learning”, IEEE International Geoscience and Remote Sensing Symposium (IGRASS), (EI).

  • [11] Z. Peng, G. Wang, X. Zhang, X. Tang, L. Gao, L. Jiao, “A Learnable Blur Kernel for Remote Sensing Image Retrieval”, IEEE International Geoscience and Remote Sensing Symposium (IGRASS), (EI).

  • [12] T. Zhang, X. Zhang, X. Zhu, G. Wang, X. Han, X. Tang, L. Jiao, “Multistage Enhancement Network for Tiny Object Detection in Remote Sensing Images”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2).

    • Reviewer

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