Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion

• URL: http://arxiv.org/abs/2303.10991v1
• Date: Mon, 20 Mar 2023 10:19:50 GMT
• Title: Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion
• Authors: Jinyoung Jun, Jae-Han Lee, and Chang-Su Kim
• Abstract summary: We propose a versatile depth estimator (VDE) composed of a common relative depth estimator (CRDE) and multiple relative-to-metric converters (R2MCs) The proposed VDE can cope with diverse scenes, including both indoor and outdoor scenes, with only a 1.12% parameter increase per camera. Experimental results demonstrate that VDE supports multiple cameras effectively and efficiently and also achieves state-of-the-art performance in the conventional single-camera scenario.
• Score: 36.36012484044768
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a versatile depth estimator (VDE), composed of a common relative depth estimator (CRDE) and multiple relative-to-metric converters (R2MCs). The CRDE extracts relative depth information, and each R2MC converts the relative information to predict metric depths for a specific camera. The proposed VDE can cope with diverse scenes, including both indoor and outdoor scenes, with only a 1.12\% parameter increase per camera. Experimental results demonstrate that VDE supports multiple cameras effectively and efficiently and also achieves state-of-the-art performance in the conventional single-camera scenario.

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