SSMB: Self-Supervised Keypoint Detection Directly on Motion-Blurred Images
zhenjun_zhao · x · 2026-08-28
New paper SSMB introduces a self-supervised keypoint detector that works directly on motion-blurred images—no deblurring preprocessing, no handcrafted detector, no external pseudo-labels.
Key component: a Local Discriminability Enhancement (LDE) module restores fine local structure after global feature mixing. Training runs in two self-supervised stages: geometric pretraining on synthetic shapes, then blur-aware training on real sharp/blurred pairs. Code, models and datasets will be released upon acceptance.
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