About me (Curriculum Vitae)

Dr. Xiang Li is a Lecturer in the Department of Computer Science at the University of Reading. His research focuses on multimodal large language models, computer vision, and remote sensing data processing. Dr. Li has published over 50 papers in top conferences and journals in computer vision and remote sensing, including CVPR, ICCV, NeurIPS, TVCG, and TGRS, with 5000+ citations on Google Scholar and an h-index of 25. He collaborates with leading researchers from institutions such as the TUM, NYU, KAUST, WHU, and AIR CAS. Dr. Li was involved in the MiniGPT-4 project (>25k stars on GitHub) and served as a guest editor for the IEEE GRSM special issue on “Vision-Language Models in Remote Sensing.” His research aims to drive innovation in AI technologies for Earth observation and practical applications. Dr Li got his Bachelor’s degree from Wuhan University in 2014 and his PhD degree from the Aerospace Information Research Institute, Chinese Academy of Sciences in 2019.

🔥Hiring PhD Students and Interns: welcome enthusiastic students passionate about computer vision, multimodal large language models, and remote sensing to apply for PhD positions and internships.

🔥 News

[12/2024] Opening position: One fully funded PhD position in AI for Bioversity.
[10/2024] I join the University of Reading as a Lecturer in Computer Science.
[09/2024] Two papers accepted at NeruIPS 2024 Datasets and Benchmarks Track (VRSBench and 3DCoMPaT200).
[07/2024] One paper on 3D LLM (Uni3DL) is accepted by ECCV 2024.
[07/2024] I will serve as the Guest Editor for the special issue “Vision-Language Models in Remote Sensing” at IEEE GRSM.
[06/2024] I’m co-organizing the C3DV: 2nd Workshop on Compositional 3D Vision at CVPR 2024.
[05/2024] One paper on few-shot object detection (InfRS) is accepted by TGRS.
[05/2024] One paper on CO2 mapping is published at JAG.
[04/2024] The first review paper on vision-language models in remote sensing is published at IEEE GRSM.
[11/2023] One paper on CLIP-based RS scene classification (RS-CLIP) is published at JAG.
[07/2023] We release RSGPT, the first GPT-based multimodal LLM in remote sensing.
[05/2025] We release the review paper on vision-language models in remote sensing.

Selected Publications

[# denotes equal contribution, * denotes corresponding author]

	MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models. Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny. arxiv, 2023 [project] [paper] [code] [huggingface demo]
	MiniGPT-v2: Large Language Model as a Unified Interface for Vision-Language Multi-task Learning. Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, Mohamed Elhoseiny. arxiv, 2023 [project] [paper] [code] [huggingface demo]
	Vision-Language Models in Remote Sensing: Current Progress and Future Trends. Xiang Li, Congcong Wen, Yuan Hu, Zhengpeng Yuan, Xiao Xiang Zhu. IEEE Geoscience and Remote Sensing Magazine (GRSM)*, 2024 [paper]
	RSGPT: A Remote Sensing Vision Language Model and Benchmark. Yuan Hu, Jianlong Yuan, Congcong Wen, Xiaonan Lu, Xiang Li. arxiv*, 2023 [project] [paper] [code]
	RS-CLIP: Zero Shot Remote Sensing Scene Classification via Contrastive Vision-Language Supervision. Xiang Li, Xiang Li, Congcong Wen, Nan Zhou. International Journal of Applied Earth Observation and Geoinformation (JAG), 2023 [project] [paper] [code]
	Few-shot Object Detection on Remote Sensing Images. Xiang Li^#, Jingyu Deng^#, Yi Fang. TGRS, 2021 [paper] [code]
	Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification. Xiang Li, Lingjing Wang, Mingyang Wang, Congcong Wen, Nan Zhou, Yi Fang. ISPRS JPRS, 2021 [paper]
	Topology Constrained Shape Correspondence. Xiang Li^#, Congcong Wen^#, Lingjing Wang, Yi Fang. TVCG, 2020 [paper] [code]
	Few-shot Learning of Part-specific Probability Space for 3D Shape Segmentation. Lingjing Wang^#, Xiang Li^#, Yi Fang. CVPR, 2020 [paper] [code]
	Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification. Congcong Wen, Lina Yang, Ling Peng, Xiang Li* ISPRS JPRS, 2020 [paper] [code]

Honors and Awards

Outstanding Reviewer for ICCV 2021.
Postdoc Non-travel Award, NYUAD 2020 & 2021.
National Scholarship, University of Chinese Academy of Sciences, 2018
China Scholarship Council (CSC) scholarship, 2017
Director’s Fund of RADI, 2017
Seagate Scholarship, Wuhan University, 2012
National Scholarship, Wuhan University, 2011

Xiang Li

Selected Publications

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

MiniGPT-v2: Large Language Model as a Unified Interface for Vision-Language Multi-task Learning.

Vision-Language Models in Remote Sensing: Current Progress and Future Trends.

RSGPT: A Remote Sensing Vision Language Model and Benchmark.

RS-CLIP: Zero Shot Remote Sensing Scene Classification via Contrastive Vision-Language Supervision.

Few-shot Object Detection on Remote Sensing Images.

Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification.

Topology Constrained Shape Correspondence.

Few-shot Learning of Part-specific Probability Space for 3D Shape Segmentation.

Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification.

Honors and Awards