Dynamic Context Correspondence Network for Semantic Alignment

ICCV 2019 Shuaiyi HuangQiuyue WangSongyang ZhangShipeng YanXuming He

Establishing semantic correspondence is a core problem in computer vision and remains challenging due to large intra-class variations and lack of annotated data. In this paper, we aim to incorporate global semantic context in a flexible manner to overcome the limitations of prior work that relies on local semantic representations... (read more)

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