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

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

14 Dec 2023arXiv:2312.09254archive 2025-07-28

Luca Bartolomei, Matteo Poggi, Andrea Conti, Fabio Tosi, Stefano Mattoccia

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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Depth CompletionDomain GeneralizationStereo Matching

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