Guangqian Guo  

Biography

I am currently a second-year Ph.D. student at the Unmanned Systems Technology Research Institute, Northwestern Polytechnical University (NWPU). The outline of my experience is as follows:

07/2024--04/2025: Research intern, at Huawei Shanghai Research Institute.

03/2023--Present: Ph.D., at Northwestern Polytechnical University, Xi'an, China.

09/2021--03/2023: M.S., at Northwestern Polytechnical University, Xi'an, China.

09/2017--07/2021: B.S., rank: 1/144, at Shannxi University of Science and Technology, Xi'an, China.

My research primarily focuses on developing more robust and accurate visual foundation models and multimodal large language models for visual object perception and understanding. My work has been published in several top-tier conferences and journals, including CVPR, ECCV, IJCAI, TNNLS, TCSVT, etc.

More recently, I mainly focus on improving the robustness and generalization of visual foundation models, such as Segment Anything Model (SAM). I have also been working on enhancing the performance of multimodal large language models in perception tasks.

I am actively looking for a research internship position related to AIGC and Multimodal Large Language Models.

Recent News

06/2026 I will attend VALSE 2025 in Zhuhai and give a poster presentation.

02/2025 I have one conference paper (GleSAM) (first author) accepted by CVPR (CCF-A).

12/2024 I have one journal paper (SAM-COD+) accepted by TCSVT (中科院 Q1, IF=8.4).

07/2024 I have two conference paper (SAM-COD and P-COD) accepted by ECCV-24.

04/2024 I have one conference paper (P2P) (first author) accepted by IJCAI-24 (CCF-A).

02/2024 I have one journal paper (co-first author) accepted by TGRS (中科院 Q1, IF=8.2).

05/2023 I have one journal paper (first author) accepted by TCSVT (中科院 Q1, IF=8.4).

01/2023 I have one journal paper accepted by TNNLS (中科院 Q1, CCF-B, IF=10.4).

Publications

	Guangqian Guo, Yong Guo, Xuehui Yu, Wenbo Li, Yaoxing Wang, Shan Gao Segment Any-Quality Images with Generative Latent Space Enhancement IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2025 [Paper] [Code]
	Guangqian Guo, Dian Shao, Chenguang Zhu, Sha Meng, Xuan Wang, Shan Gao P2P: Transforming from Point Supervision to Explicit Visual Prompt for Object Detection and Segmentation INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), 2024 [Paper] [Code]
	Guangqian Guo, Pengfei Chen, Xuehui Yu, Zhenjun Han, Qixiang Ye, Shan Gao HANet: Save the Tiny, Save the All: Hierarchical Activation Network for Tiny Object Detection IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023 [Paper] [Code]
	*Chaowei Wang, *Guangqian Guo, Chang Liu, Dian Shao, Shan Gao Effective Rotate: Learning Rotation-robust Prototype for Aerial Object Detection * co-first author IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2024 [Paper]
	Shan Gao (Ph.D. advisor), *Guangqian Guo, Hanqiao Huang, C. L. Philip Chen Go deep or broad? Exploit hybrid network architecture for weakly supervised object classification and localization * student first author IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 [Paper]
	Huafeng Chen, Pengxu Wei, Guangqian Guo, Shan Gao SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detection European Conference on Computer Vision (ECCV), 2024 [Paper]
	Huafeng Chen, Dian Shao, Guangqian Guo, Shan Gao Just a Hint: Point-Supervised Camouflaged Object Detection European Conference on Computer Vision (ECCV), 2024 [Paper]
	Shan Gao, Guangqian Guo, C. L. Philip Chen Event-Based Incremental Broad Learning System for Object Classification IEEE International Conference on Computer Vision Workshop (ICCVW), 2019

Awards

National Scholarship (recevied twice), 2018, 2024

The First Prize Scholarship for Ph.D. of Northwestern Polytechnical University, 2023

Outstanding Graduates of Colleges and Universities in Shaanxi Province, 2021