6 citations · 9 across the 2 of their papers we have counts for
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cs.CV2025
PromptMID: Modal Invariant Descriptors Based on Diffusion and Vision Foundation Models for Optical-SAR Image Matching
Han Nie, Bin Luo, Jun Liu +4
The ideal goal of image matching is to achieve stable and efficient performance in unseen domains. However, many existing learning-based optical-SAR image matching methods, despite…
cs.CV2020★ 3 cited
Object Detection based on OcSaFPN in Aerial Images with Noise
Chengyuan Li, Jun Liu, Hailong Hong +5
Taking the deep learning-based algorithms into account has become a crucial way to boost object detection performance in aerial images. While various neural network representations…
cs.CV2020★ 6 cited
Can Synthetic Data Improve Object Detection Results for Remote Sensing Images?
Weixing Liu, Jun Liu, Bin Luo
Deep learning approaches require enough training samples to perform well, but it is a challenge to collect enough real training data and label them manually. In this letter, we pro…