📝 Publications

My full paper list can be found at .

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RSMamba: Remote Sensing Image Classification with State Space Model
GRSL, 2024
Keyan Chen, Bowen Chen, Chenyang Liu, Wenyuan Li, Zhengxia Zou, and Zhenwei Shi
Popular Article of GRSL
[Arxiv] [Github]

We introduce RSMamba, a novel architecture for remote sensing image classification. RSMamba is based on the State Space Model (SSM) and incorporates an efficient, hardware-aware design known as the Mamba. To overcome the limitation of the vanilla Mamba, which can only model causal sequences and is not adaptable to two-dimensional image data, we propose a dynamic multi-path activation mechanism to augment Mamba's capacity to model non-causal data.
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Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection
IGARSS, 2024
Keyan Chen, Chenyang Liu, Wenyuan Li, Zili Liu, Hao Chen, Haotian Zhang, Zhengxia Zou, and Zhenwei Shi
[Arxiv] [Github] [Page] [Demo]

We integrate the latent knowledge of the SAM foundation model into change detection, effectively addressing the domain shift in general knowledge transfer and the challenge of expressing homogeneous and heterogeneous characteristics of multi-temporal images.
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RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model
IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2024
Keyan Chen, Chenyang Liu, Hao Chen, Haotian Zhang, Wenyuan Li, Zhengxia Zou, and Zhenwei Shi
🏆️ ESI Highly Cited Paper & ESI Hot Paper
Popular Article of TGRS
[Arxiv] [Github] [Page] [Demo]

We consider designing an automated instance segmentation approach for remote sensing images based on the SAM foundation model, incorporating semantic category information with prompt learning.
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Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function Space
IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023
Keyan Chen, Wenyuan Li, Sen Lei, Jianqi Chen, Xiaolong Jiang, Zhengxia Zou, and Zhenwei Shi
[Arxiv] [Github] [Page] [Demo]

We propose a new super-resolution framework based on context interaction in implicit function space for learning continuous representations of remote sensing images, called FunSR, which consists of three main components: a functional representor, a functional interactor, and a functional parser.
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Object Detection in 20 Years: A Survey
Proceedings of the IEEE (P IEEE), 2023
Zhengxia Zou, Keyan Chen, Zhenwei Shi, Yuhong Guo and Jieping Ye
🏆️ ESI Highly Cited Paper & ESI Hot Paper
Popular Article of P IEEE
[PDF] [Github] [Page]

This paper extensively reviews the fast-moving research field in the light of technical evolution, spanning over a quarter-century's time (from the 1990s to 2022). A number of topics have been covered, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speed-up techniques, and the recent state-of-the-art detection methods.
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Resolution-agnostic Remote Sensing Scene Classification with Implicit Neural Representations
IEEE Geoscience and Remote Sensing Letters (GRSL), 2022
Keyan Chen, Wenyuan Li, Jianqi Chen, Zhengxia Zou and Zhenwei Shi
[PDF] [Github] [Page]

We propose a novel scene classification method with scale and resolution adaptation ability. Unlike previous CNNbased methods that make predictions based on rasterized image inputs, the proposed method converts the images as continuous functions with INRs optimization and then performs classification within the function space.
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Building Extraction from Remote Sensing Images with Sparse Token Transformers
Remote Sensing, 2021
Keyan Chen, Zhengxia Zou and Zhenwei Shi
[PDF] [Github] [Page] [Demo]

We propose STT to explore the potential of using transformers for efficient building extraction. STT conducts an efficient dual-pathway transformer that learns the global semantic information in both their spatial and channel dimensions and achieves state-of-the-art accuracy on two building extraction benchmarks.