AI RESEARCH
OASIC: Occlusion-Agnostic and Severity-Informed Classification
arXiv CS.LG
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ArXi:2604.04012v1 Announce Type: cross Severe occlusions of objects pose a major challenge for computer vision. We show that two root causes are (1) the loss of visible information and (2) the distracting patterns caused by the occluders. Our approach addresses both causes at the same time. First, the distracting patterns are removed at test-time, via masking of the occluding patterns. This masking is independent of the type of occlusion, by handling the occlusion through the lens of visual anomalies w.r.t. the object of interest.