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

arXiv 2107.07330 ↗First posted 15 Jul 2021cs.CVcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 42 of its 67 references that are in the map. First posted on arXiv 15 Jul 2021.

Builds on

42 of 67 references.

References · 42

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30 more
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Citing papers per year: 2025: 2.

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