EpiMask: Leveraging Epipolar Distance Based Masks in Cross-Attention for Satellite Image Matching
The deep-learning based image matching networks can now handle significantly larger variations in viewpoints and illuminations while providing matched pairs of pixels with sub-pixel precision. These networks have been trained with ground-based image datasets and, implicitly, their performance is optimized for the pinhole camera geometry. Consequently, you get suboptimal performance when such networks are used to match satellite images since those images are synthesized as a moving satellite camera records one line at a time of the points on the ground. In this paper, we present EpiMask, a semi-dense image matching network for satellite images that (1) Incorporates patch-wise affine approx...
| Authors | Rahul Deshmukh, Aditya Chauhan, Avinash Kak |
|---|---|
| Primary category | cs.CV |
| Published | 23 March 2026 |
| Last updated at source | 30 June 2026 |
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