AI RESEARCH
Who Handles Orientation? Investigating Invariance in Feature Matching
arXiv CS.CV
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ArXi:2604.11809v1 Announce Type: new Finding matching keypoints between images is a core problem in 3D computer vision. However, modern matchers struggle with large in-plane rotations. A straightforward mitigation is to learn rotation invariance via data augmentation. However, it remains unclear at which stage rotation invariance should be incorporated. In this paper, we study this in the context of a modern sparse matching pipeline. We perform extensive experiments by