Tianyu Xin — accepted AI-conference papers

2026

SWIFT：A General Sensitive Weight Identification Framework for Fast Sensor-Transfer Pansharpening

Zeyu Xia, Chenxi Sun, Tianyu Xin, Yubo Zeng, Haoyu Chen, Liang-Jian Deng

AAAI 2026technical

Although deep learning-based methods have achieved promising performance in Pansharpening, they generally suffer from severe performance degradation when applied to data from unseen sensors. Existing cross-domain strategies, including retraining, fine-tuning, and zero-shot methods, fail to simultane

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2026

Training and Inference Within 1 Second – Tackle Cross-Sensor Degradation of Real-World Pansharpening with Efficient Residual Feature Tailoring

Tianyu Xin, Jin-Liang Xiao, Zeyu Xia, Shan Yin, Liang-Jian Deng

AAAI 2026technical

Deep learning methods for pansharpening have advanced rapidly, yet models pretrained on data from a specific sensor often generalize poorly to data from other sensors. Existing methods to tackle such cross-sensor degradation include retraining model or zero-shot methods, but they are highly time-con

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