Improving Cross-View Matching with Self-Supervised Learning
J. Cui (TU Delft - Mechanical Engineering)
Z. Xia – Mentor (TU Delft - Mechanical Engineering)
J.F.P. Kooij – Mentor (TU Delft - Mechanical Engineering)
L. Nan – Graduation committee member (TU Delft - Architecture and the Built Environment)
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Abstract
We explored the possibility of improving cross-view matching performance with self-supervised learning techniques and perform interpretations in terms of the embedding space of image features. The effect of pre-training by contrastive learning is verified quantitatively by experiments, and also exhibited by visualization of the feature space.