DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation

• URL: http://arxiv.org/abs/2107.07330v1
• Date: Thu, 15 Jul 2021 13:53:10 GMT
• Title: DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation
• Authors: Jake Deane, Sinead Kearney, Kwang In Kim, Darren Cosker
• Abstract summary: We introduce a parametric canine model, DynaDog+T, for generating synthetic canine images and data. We use this data for a common computer vision task, binary segmentation, which would otherwise be difficult due to the lack of available data.
• Score: 23.725295519857976
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Synthetic data is becoming increasingly common for training computer vision models for a variety of tasks. Notably, such data has been applied in tasks related to humans such as 3D pose estimation where data is either difficult to create or obtain in realistic settings. Comparatively, there has been less work into synthetic animal data and it's uses for training models. Consequently, we introduce a parametric canine model, DynaDog+T, for generating synthetic canine images and data which we use for a common computer vision task, binary segmentation, which would otherwise be difficult due to the lack of available data.

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