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Qi Ming (明 奇) |
News
- [2024.07] Received the Outstanding Doctoral Dissertation Award from Beijing Institute of Technology.
- [2024.05] Awarded the Excellent Doctoral Dissertation Seed Fund.
- [2024.05] One paper is accepted by TGRS.
- [2024.02] One paper is accepted by TGRS.
- [2023.10] One paper is accepted by LSP.
- [2023.09] One collaborative paper is accepted by LGRS.
- [2023.08] One collaborative paper is accepted by TGRS.
- [2023.02] One paper is accepted by CVPR 2023.
- [2023.01] One paper is accepted by ISPRS&RS.
- [2022.11] One collaborative paper is accepted by JSTARS.
- [2021.10] One collaborative paper is accepted by NeurIPS 2021.
- [2021.10] One paper is accepted by LGRS.
- [2021.07] One paper is accepted by Remote Sensing.
- [2021.07] One paper is accepted by TGRS.
- [2021.05] One collaborative paper is accepted by ICML 2021.
- [2020.12] One paper is accepted by AAAI 2021.
Short Bio
I am a PhD graduate from at Beijing Institute of Technology (BIT), and my supervisor is Prof. Lingjuan Miao. My research interests are mainly in generic object detection, oriented object detection, remote sensing, and deep learning theory. Recently, I'm working on probabilistic graphical model and 3D object detection.Education
- 2022.9 - 2023.9 Visiting Ph.D student in GAIM lab at Ghent University, supervised by Prof. Aleksandra Pizurica.
- 2019.9 - 2024.7 Ph.D in School of Automation, Beijing Institute of Technology, supervised by Prof. Lingjuan Miao.
- 2018.9 - 2019.6 M.E. in School of Automation, Beijing Institute of Technology, supervised by Prof. Lingjuan Miao.
- 2014.9 - 2018.6 B.E. in School of Automation, Beijing Institute of Technology.
Publications
Journal papers:
[1] Q. Ming, L. Miao, Z. Zhou, J. Song, Y. Dong, X. Yang, “Task Interleaving and Orientation Estimation for High-Precision Oriented Object Detection in Aerial Images”, ISPRS Journal of Photogrammetry and Remote Sensing (ISPRS&RS), (SCI Q1 Top, IF=12.7) (ESI Highly Cited Paper) [Url] [PDF] [Code] [BibTex]
[2] Q. Ming, L. Miao, Z. Zhou, Y. Dong, “CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2), (ESI Highly Cited Paper) [Url] [PDF] [Code] [BibTex]
[3] Q. Ming, L. Miao, Z. Zhou, J. Song, A. Pizurica, “Gradient Calibration Loss for Fast and Accurate Oriented Bounding Box Regression”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2), [Url] [PDF] [Code] [BibTex]
[4] Q. Ming, L. Miao, Z. Zhou, N. Vercheval, A. Pizurica, “Not All Boxes Are Equal: Learning to Optimize Bounding Boxes With Discriminative Distributions in Optical Remote Sensing Images”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2), [Url] [PDF] [BibTex]
[5] Q. Ming, L. Miao, Z. Zhou, J. Song, X. Yang, “Sparse Label Assignment for Oriented Object Detection in Aerial Images”, Remote Sensing (RS), (SCI Q2, IF=5.0) [PDF] [Code] [BibTex]
[6] Q. Ming, L. Miao, Z. Zhou, X. Yang, Y. Dong, “Optimization for Arbitrary-Oriented Object Detection via Representation Invariance Loss”, IEEE Geoscience and Remote Sensing Letters (LGRS), (SCI Q2, IF=4.8) [Url] [PDF] [Code] [BibTex]
[7] Q. Ming, X. Xiao, “Towards Accurate Medical Image Segmentation with Gradient-optimized Dice Loss”, IEEE Signal Processing Letters (LSP), (SCI Q2, IF=3.9) [Url] [PDF] [BibTex]
[8] J. Song, L. Miao, Q. Ming, Z. Zhou, Y. Dong, “Fine-Grained Object Detection in Remote Sensing Images Via Adaptive Label Assignment and Refined-Balanced Feature Pyramid Network”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), (SCI Q3, IF=5.5) [Url] [PDF] [BibTex]
[9] Y. Qiao, L. Miao, Z. Zhou, Q. Ming, “A Novel Object Detector Based on High-quality Rotation Proposal Generation and Adaptive Angle Optimization”, IEEE Transactions on Geoscience and Remote Sensing (TGRS), (SCI Q1 Top, IF=8.2), [Url] [PDF] [Code] [BibTex]
[10] J. Song, L. Miao, Z. Zhou, Q. Ming, Y. Dong, “Optimized Point Set Representation for Oriented Object Detection in Remote Sensing Images”, IEEE Geoscience and Remote Sensing Letters (LGRS), (SCI Q1 Top, IF=4.8), [Url] [PDF] [BibTex]
Conference papers:
[1] Q. Ming, L. Miao, Z. Ma, L. Zhao, Z. Zhou, X. Huang, Y. Chen, Y. Guo, “Deep Dive into Gradients: Better Optimization for 3D Object Detection with Gradient-Corrected IoU Supervision”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, (CVPR-23), in Vancouver, Canada, 2023. (CCF-A) [PDF] [Code] [BibTex] [Poster]
[2] Q. Ming, Z. Zhou, L. Miao, H. Zhang, L. Li, “Dynamic Anchor Learning for Arbitrary-Oriented Object Detection”, Proceedings of the Thirty-Five AAAI Conference on Artificial Intelligence, (AAAI-21), in Vancouver, Canada, 2021. (CCF-A) [PDF] [Code] [BibTex] [Slides] [Poster]
[3] X. Yang, J. Yan, Q. Ming, W. Wang, X. Zhang, Q. Tian, “Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss”, Proceedings of the Thirty-eighth International Conference on Machine Learning, (ICML-21), in Vienna, Austria, 2021. (CCF-A) [PDF] [Code] [BibTex]
[4] X. Yang, X. Yang, J. Yang, Q. Ming, W. Wang, Q. Tian, J. Yan, “Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence”, Proceedings of the Thirty-fifth Annual Conference on Neural Information Processing Systems, (NeurIPS-21), Virtual Conference, 2021. (CCF-A) [PDF] [Code] [BibTex]
Awards
Services
Journal Reviewer:
Conference Reviewer: