Guided Semantic Flow

ECCV 2020 Sangryul JeonDongbo MinSeungryong KimJihwan ChoeKwanghoon Sohn

Establishing dense semantic correspondences requires dealing with large geometric variations caused by the unconstrained setting of images. To address such severe matching ambiguities, we introduce a novel approach, called {guided semantic flow}, based on the key insight that sparse yet reliable matches can effectively capture non-rigid geometric variations, and these confident matches can guide adjacent pixels to have similar solution spaces, reducing the matching ambiguities significantly... (read more)

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