Publications

2025

1. Hilbert Curve-Encoded Rotation-Equivariant Oriented Object Detector with Locality-Preserving Spatial Mapping

   Qi Ming^† , Liuqian Wang^†, Juan Fang, Xudong Zhao, Yucheng Xu, Ziyi Teng, Yue Zhou, Xiaoxi Hu, and 2 more authors

   In Proceedings of the AAAI conference on artificial intelligence, 2025

   Bib HTML PDF Code Poster Slides

   @inproceedings{ming2025hilbert,
     title = {Hilbert Curve-Encoded Rotation-Equivariant Oriented Object Detector with Locality-Preserving Spatial Mapping},
     author = {Ming, Qi and Wang, Liuqian and Fang, Juan and Zhao, Xudong and Xu, Yucheng and Teng, Ziyi and Zhou, Yue and Hu, Xiaoxi and Zhang, Xiaohan and Guo, Yufei},
     booktitle = {Proceedings of the AAAI conference on artificial intelligence},
     year = {2025},
     highlights = {(CCF-A)},
   }

2. Learning Better UAV-Based Cross-View Object Geo-Localization from Multi-Modal Prompts: MoP-UAV Benchmark and MoPT Framework

   Xiaohan Zhang, Zhangkai Shen, Siyuan Cao, Xiaokai Bai, Yiming Li, Zheheng Han, Zhe Wu,  Qi Ming , and 1 more author

   In Proceedings of the AAAI conference on artificial intelligence, 2025

   Bib HTML PDF Poster Slides

   @inproceedings{zhang2025learning,
     title = {Learning Better UAV-Based Cross-View Object Geo-Localization from Multi-Modal Prompts: MoP-UAV Benchmark and MoPT Framework},
     author = {Zhang, Xiaohan and Shen, Zhangkai and Cao, Siyuan and Bai, Xiaokai and Li, Yiming and Han, Zheheng and Wu, Zhe and Ming, Qi and Shen, Huiliang},
     booktitle = {Proceedings of the AAAI conference on artificial intelligence},
     year = {2025},
     highlights = {(CCF-A)},
   }

3. Unified Five-distance Bounding Box Representation for Remote Sensing Oriented Object Detection

   Yajun Qiao, Lingjuan Miao, Zhiqiang Zhou,  Qi Ming , and Yuhao Wang

   IEEE Transactions on Geoscience and Remote Sensing, vol., no., pp.1-1, 2025

   Bib HTML Code

   @article{qiao2025unified,
     author = {Qiao, Yajun and Miao, Lingjuan and Zhou, Zhiqiang and Ming, Qi and Wang, Yuhao},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     title = {Unified Five-distance Bounding Box Representation for Remote Sensing Oriented Object Detection},
     year = {2025},
     volume = {},
     number = {},
     pages = {1-1},
     publisher = {IEEE},
   }

2024

1. Gradient Calibration Loss for Fast and Accurate Oriented Bounding Box Regression

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, Junjie Song, and Aleksandra Pizurica

   IEEE Transactions on Geoscience and Remote Sensing, vol.62, no., pp.1-15, 2024

   Bib HTML PDF Code

   @article{ming2024gradient,
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Song, Junjie and Pizurica, Aleksandra},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     title = {Gradient Calibration Loss for Fast and Accurate Oriented Bounding Box Regression},
     year = {2024},
     volume = {62},
     number = {},
     pages = {1-15},
     publisher = {IEEE},
     keywords = {Object detection;Convergence;Remote sensing;Detectors;Training;Feature extraction;Proposals;Convolutional neural network;gradient analysis;loss function;oriented object detection},
   }

2. Not All Boxes Are Equal: Learning to Optimize Bounding Boxes With Discriminative Distributions in Optical Remote Sensing Images

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, Nicolas Vercheval, and Aleksandra Pižurica

   IEEE Transactions on Geoscience and Remote Sensing, vol.62, no., pp.1-14, 2024

   Bib HTML PDF

   @article{ming2024not,
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Vercheval, Nicolas and Pižurica, Aleksandra},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     title = {Not All Boxes Are Equal: Learning to Optimize Bounding Boxes With Discriminative Distributions in Optical Remote Sensing Images},
     year = {2024},
     volume = {62},
     number = {},
     pages = {1-14},
     publisher = {IEEE},
     keywords = {Detectors;Remote sensing;Feature extraction;Object detection;Training;Optimization;Location awareness;Anchor refinement;bounding box regression;convolutional neural networks (CNNs);feature alignment;object detection},
   }

2023

1. Towards accurate medical image segmentation with gradient-optimized dice loss

   Qi Ming , and Xiaowu Xiao

   IEEE Signal Processing Letters, vol.31, pp.191–195, 2023

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   @article{ming2023towards,
     title = {Towards accurate medical image segmentation with gradient-optimized dice loss},
     author = {Ming, Qi and Xiao, Xiaowu},
     journal = {IEEE Signal Processing Letters},
     volume = {31},
     pages = {191--195},
     year = {2023},
     publisher = {IEEE},
   }

2. Task Interleaving and Orientation Estimation for High-precision Oriented Object Detection in Aerial Images

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, Junjie Song, Yunpeng Dong, and Xue Yang

   ISPRS Journal of Photogrammetry and Remote Sensing, vol.196, pp.241-255, 2023

   Bib HTML PDF Code

   @article{ming2023task,
     title = {Task Interleaving and Orientation Estimation for High-precision Oriented Object Detection in Aerial Images},
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Song, Junjie and Dong, Yunpeng and Yang, Xue},
     journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
     volume = {196},
     pages = {241-255},
     year = {2023},
     publisher = {Elsevier},
     issn = {0924-2716},
     highlights = {(ESI Highly Cited Paper)},
   }

3. Deep Dive into Gradients: Better Optimization for 3D Object Detection with Gradient-Corrected IoU Supervision

   Qi Ming , Lingjuan Miao, Zhe Ma, Lin Zhao, Zhiqiang Zhou, Xuhui Huang, Yuanpei Chen, and Yufei Guo

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.5136–5145, 2023

   Bib HTML PDF Code Poster

   @inproceedings{ming2023deep,
     title = {Deep Dive into Gradients: Better Optimization for 3D Object Detection with Gradient-Corrected IoU Supervision},
     author = {Ming, Qi and Miao, Lingjuan and Ma, Zhe and Zhao, Lin and Zhou, Zhiqiang and Huang, Xuhui and Chen, Yuanpei and Guo, Yufei},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
     pages = {5136--5145},
     year = {2023},
     highlights = {(CCF-A)},
   }

4. A novel object detector based on high-quality rotation proposal generation and adaptive angle optimization

   Yajun Qiao, Lingjuan Miao, Zhiqiang Zhou, and  Qi Ming

   IEEE Transactions on Geoscience and Remote Sensing, vol.61, pp.1–15, 2023

   Bib HTML PDF

   @article{qiao2023novel,
     title = {A novel object detector based on high-quality rotation proposal generation and adaptive angle optimization},
     author = {Qiao, Yajun and Miao, Lingjuan and Zhou, Zhiqiang and Ming, Qi},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     volume = {61},
     pages = {1--15},
     year = {2023},
     publisher = {IEEE},
   }

5. Optimized Point Set Representation for Oriented Object Detection in Remote-Sensing Images

   Junjie Song, Lingjuan Miao, Zhiqiang Zhou,  Qi Ming , and Yunpeng Dong

   IEEE Geoscience and Remote Sensing Letters, vol.20, pp.1–5, 2023

   Bib HTML PDF

   @article{song2023optimized,
     title = {Optimized Point Set Representation for Oriented Object Detection in Remote-Sensing Images},
     author = {Song, Junjie and Miao, Lingjuan and Zhou, Zhiqiang and Ming, Qi and Dong, Yunpeng},
     journal = {IEEE Geoscience and Remote Sensing Letters},
     volume = {20},
     pages = {1--5},
     year = {2023},
     publisher = {IEEE},
   }

2022

1. Fine-grained object detection in remote sensing images via adaptive label assignment and refined-balanced feature pyramid network

   Junjie Song, Lingjuan Miao,  Qi Ming , Zhiqiang Zhou, and Yunpeng Dong

   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.16, pp.71–82, 2022

   Bib HTML PDF

   @article{song2022fine,
     title = {Fine-grained object detection in remote sensing images via adaptive label assignment and refined-balanced feature pyramid network},
     author = {Song, Junjie and Miao, Lingjuan and Ming, Qi and Zhou, Zhiqiang and Dong, Yunpeng},
     journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
     volume = {16},
     pages = {71--82},
     year = {2022},
     publisher = {IEEE},
   }

2021

1. CFC-Net: A critical feature capturing network for arbitrary-oriented object detection in remote-sensing images

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, and Yunpeng Dong

   IEEE Transactions on Geoscience and Remote Sensing, vol.60, pp.1–14, 2021

   Bib HTML PDF Code

   @article{ming2021cfc,
     title = {CFC-Net: A critical feature capturing network for arbitrary-oriented object detection in remote-sensing images},
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Dong, Yunpeng},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     volume = {60},
     pages = {1--14},
     year = {2021},
     publisher = {IEEE},
     highlights = {(ESI Highly Cited Paper)},
   }

2. Dynamic anchor learning for arbitrary-oriented object detection

   Qi Ming , Zhiqiang Zhou, Lingjuan Miao, Hongwei Zhang, and Linhao Li

   In Proceedings of the AAAI conference on artificial intelligence, vol.35, no.3, pp.2355–2363, 2021

   Bib HTML PDF Code Poster Slides

   @inproceedings{ming2021dynamic,
     title = {Dynamic anchor learning for arbitrary-oriented object detection},
     author = {Ming, Qi and Zhou, Zhiqiang and Miao, Lingjuan and Zhang, Hongwei and Li, Linhao},
     booktitle = {Proceedings of the AAAI conference on artificial intelligence},
     volume = {35},
     number = {3},
     pages = {2355--2363},
     year = {2021},
     highlights = {(CCF-A)},
   }

3. Optimization for arbitrary-oriented object detection via representation invariance loss

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, Xue Yang, and Yunpeng Dong

   IEEE Geoscience and Remote Sensing Letters, vol.19, pp.1–5, 2021

   Bib HTML PDF

   @article{ming2021optimization,
     title = {Optimization for arbitrary-oriented object detection via representation invariance loss},
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Yang, Xue and Dong, Yunpeng},
     journal = {IEEE Geoscience and Remote Sensing Letters},
     volume = {19},
     pages = {1--5},
     year = {2021},
     publisher = {IEEE},
   }

4. Sparse label assignment for oriented object detection in aerial images

   Qi Ming , Lingjuan Miao, Zhiqiang Zhou, Junjie Song, and Xue Yang

   Remote Sensing, vol.13, no.14, pp.2664, 2021

   Bib HTML PDF

   @article{ming2021sparse,
     title = {Sparse label assignment for oriented object detection in aerial images},
     author = {Ming, Qi and Miao, Lingjuan and Zhou, Zhiqiang and Song, Junjie and Yang, Xue},
     journal = {Remote Sensing},
     volume = {13},
     number = {14},
     pages = {2664},
     year = {2021},
     publisher = {MDPI},
   }

5. Learning high-precision bounding box for rotated object detection via kullback-leibler divergence

   Xue Yang, Xiaojiang Yang, Jirui Yang,  Qi Ming , Wentao Wang, Qi Tian, and Junchi Yan

   Advances in Neural Information Processing Systems, vol.34, pp.18381–18394, 2021

   Bib HTML PDF Code

   @article{yang2021learning,
     title = {Learning high-precision bounding box for rotated object detection via kullback-leibler divergence},
     author = {Yang, Xue and Yang, Xiaojiang and Yang, Jirui and Ming, Qi and Wang, Wentao and Tian, Qi and Yan, Junchi},
     journal = {Advances in Neural Information Processing Systems},
     volume = {34},
     pages = {18381--18394},
     year = {2021},
     highlights = {(CCF-A)},
   }

6. Rethinking rotated object detection with gaussian wasserstein distance loss

   Xue Yang, Junchi Yan,  Qi Ming , Wentao Wang, Xiaopeng Zhang, and Qi Tian

   In International conference on machine learning, pp.11830–11841, 2021

   Bib HTML PDF Code

   @inproceedings{yang2021rethinking,
     title = {Rethinking rotated object detection with gaussian wasserstein distance loss},
     author = {Yang, Xue and Yan, Junchi and Ming, Qi and Wang, Wentao and Zhang, Xiaopeng and Tian, Qi},
     booktitle = {International conference on machine learning},
     pages = {11830--11841},
     year = {2021},
     organization = {PMLR},
     highlights = {(CCF-A)},
   }