Cross-View Completion Models are Zero-shot Correspondence Estimators

In this work, we explore new perspectives on cross-view completion learning by drawing an analogy to self-supervised correspondence learning. Through our analysis, we demonstrate that the cross-attention map within cross-view completion models captures correspondence more effectively than other corr...

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Veröffentlicht in:	arXiv.org 2024-12
Hauptverfasser:	An, Honggyu, Kim, Jinhyeon, Park, Seonghoon, Jung, Jaewoo, Han, Jisang, Hong, Sunghwan, Kim, Seungryong
Format:	Artikel
Sprache:	eng
Schlagworte:	Learning Matching
Online-Zugang:	Volltext
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