CDPR: Cross-modal Diffusion with Polarization for Reliable Monocular Depth Estimation

CDPR is a new framework for monocular depth estimation that integrates polarization data with RGB inputs using a diffusion-based approach, enhancing robustness in complex scenarios like textureless surfaces and reflections. This method improves accuracy by dynamically fusing multi-modal information through a confidence-aware gating mechanism, making it particularly useful for developers working on advanced computer vision tasks requiring reliable depth perception.

Read the full article at arXiv cs.CV (Vision)

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