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arXiv · 2307.15988

RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid Subjects

Sascha Kirch·Valeria Olyunina·Jan Ondřej·Rafael Pagés·Sergio Martin·Clara Pérez-Molina
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Abstract

We present RGB-D-Fusion, a multi-modal conditional denoising diffusion probabilistic model to generate high resolution depth maps from low-resolution monocular RGB images of humanoid subjects. RGB-D-Fusion first generates a low-resolution depth map using an image conditioned denoising diffusion probabilistic model and then upsamples the depth map using a second denoising diffusion probabilistic model conditioned on a low-resolution RGB-D image. We further introduce a novel augmentation technique, depth noise augmentation, to increase the robustness of our super-resolution model.

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Sascha Kirch, Valeria Olyunina, Jan Ondřej, Rafael Pagés, Sergio Martin, Clara Pérez-Molina. 2023-07-29. RGB-D-Fusion: Image Conditioned Depth Diffusion of Humanoid Subjects. https://doi.org/10.1109/access.2023.3312017

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