Leveraging Monocular Disparity Estimation for Single-View Reconstruction

• URL: http://arxiv.org/abs/2207.00182v1
• Date: Fri, 1 Jul 2022 03:05:40 GMT
• Title: Leveraging Monocular Disparity Estimation for Single-View Reconstruction
• Authors: Marissa Ramirez de Chanlatte, Matheus Gadelha, Thibault Groueix, Radomir Mech
• Abstract summary: We leverage advances in monocular depth estimation to obtain disparity maps. We transform 2D normalized disparity maps into 3D point clouds by solving an optimization on the relevant camera parameters.
• Score: 8.583436410810203
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a fine-tuning method to improve the appearance of 3D geometries reconstructed from single images. We leverage advances in monocular depth estimation to obtain disparity maps and present a novel approach to transforming 2D normalized disparity maps into 3D point clouds by solving an optimization on the relevant camera parameters, After creating a 3D point cloud from disparity, we introduce a method to combine the new point cloud with existing information to form a more faithful and detailed final geometry. We demonstrate the efficacy of our approach with multiple experiments on both synthetic and real images.

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