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

• URL: http://arxiv.org/abs/2312.09254v1
• Date: Thu, 14 Dec 2023 18:59:58 GMT
• Title: Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization
• Authors: Luca Bartolomei, Matteo Poggi, Andrea Conti, Fabio Tosi, Stefano Mattoccia
• Abstract summary: This paper exploits the generalization capability of modern stereo networks to face depth completion. Any stereo network or traditional stereo matcher can be seamlessly plugged into our framework.
• Score: 40.25292494550211
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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