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arXiv · 2312.09254

Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization

Luca Bartolomei·Matteo Poggi·Andrea Conti·Fabio Tosi·Stefano Mattoccia
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Abstract

This paper proposes a new framework for depth completion robust against domain-shifting issues. It exploits the generalization capability of modern stereo networks to face depth completion, by processing fictitious stereo pairs obtained through a virtual pattern projection paradigm. Any stereo network or traditional stereo matcher can be seamlessly plugged into our framework, allowing for the deployment of a virtual stereo setup that is future-proof against advancement in the stereo field. Exhaustive experiments on cross-domain generalization support our claims. Hence, we argue that our framework can help depth completion to reach new deployment scenarios.

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Luca Bartolomei, Matteo Poggi, Andrea Conti, Fabio Tosi, Stefano Mattoccia. 2023-12-14. Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization. https://arxiv.org/abs/2312.09254

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