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Jingtao Li

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@Jingtao-Li-CVer

Research Associate at University of Cambridge (26-); My research interest is anomaly detection/foundation model/application with remote sensing images;

jingtao-li-cver.github.io/home_page/

HyperFree. This is an official implementation for "HyperFree: A Channel-adaptive and Tuning-free Foundation Model for Hyperspectral Remote Sensing Imagery" (CVPR2025)

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ASD. This is an official implementation for "Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors“ (AAAI 2023))

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TDD. This is an official implementation for "One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning“ (TGRS 2024))

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UniADRS. This is an official implementation for "Learning a Cross-Modality Anomaly Detector for Remote Sensing Imagery“ (TIP 2024))

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AnomalyCD. This is the official implementation for the paper "Unsupervised anomaly localization with high-resolution and time-series satellite imagery: from global disaster dataset to zero-shot model via SAM（ISPRS2026）".

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MMRAD. This is the official implementation for the paper "## Adapting the segment anything model for multi-modal retinal anomaly detection and localization (Information Fusion2025)".

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Adaptation_For_Instance_Anomalies. This is the official implementation for the paper "Segmenting Remote Sensing Anomalies at Instance Level via Anomaly Map-Guided Adaptation" (TGRS 2024).

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