Learning to Match Aerial Images with Deep Attentive Architectures
CVPR, pp. 3539-3547, 2016.
Image matching is a fundamental problem in Computer Vision. In the context of feature-based matching, SIFT and its variants have long excelled in a wide array of applications. However, for ultra-wide baselines, as in the case of aerial images captured under large camera rotations, the appearance variation goes beyond the reach of SIFT and...More