Cross-View Completion Models are Zero-shot Correspondence Estimators

Honggyu An; Jin Hyeon Kim; Seonghoon Park; Jaewoo Jung; Jisang Han; Sunghwan Hong; Seungryong Kim

CVPR 2025highlight2 citations

Cross-View Completion Models are Zero-shot Correspondence Estimators

Honggyu An, Jin Hyeon Kim, Seonghoon Park, Jaewoo Jung, Jisang Han, Sunghwan Hong, Seungryong Kim

Abstract

In this work, we analyze new aspects of cross-view completion, mainly through the analogy of cross-view completion and traditional self-supervised correspondence learning algorithms. Based on our analysis, we reveal that the cross-attention map of Croco-v2, best reflects this correspondence information compared to other correlations from the encoder or decoder features. We further verify the effectiveness of the cross-attention map by evaluating on both zero-shot and supervised dense geometric correspondence and multi-frame depth estimation.

BibTeX

@InProceedings{An_2025_CVPR,
    author    = {An, Honggyu and Kim, Jin Hyeon and Park, Seonghoon and Jung, Jaewoo and Han, Jisang and Hong, Sunghwan and Kim, Seungryong},
    title     = {Cross-View Completion Models are Zero-shot Correspondence Estimators},
    booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
    month     = {June},
    year      = {2025},
    pages     = {1103-1115}
}