A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
CroMo: Cross-Modal Learning for Monocular Depth Estimation
[article]
2022
arXiv
pre-print
Learning-based depth estimation has witnessed recent progress in multiple directions; from self-supervision using monocular video to supervised methods offering highest accuracy. Complementary to supervision, further boosts to performance and robustness are gained by combining information from multiple signals. In this paper we systematically investigate key trade-offs associated with sensor and modality design choices as well as related model training strategies. Our study leads us to a new
arXiv:2203.12485v2
fatcat:pcrpj4i5czcaxio6fhsaczmyrq