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Papers

D3D-HOI: Dynamic 3D Human-Object Interactions from Videos

2021-08-19 · Xiang Xu, Hanbyul Joo, Greg Mori, Manolis Savva

We introduce D3D-HOI: a dataset of monocular videos with ground truth annotations of 3D object pose, shape and part motion during human-object interactions. Our dataset consists of several common articulated objects captured from diverse real-world scenes and camera viewpoints. Each manipulated object (e.g., microwave oven) is represented with a matching 3D parametric model. This data allows us to evaluate the reconstruction quality of articulated objects and establish a benchmark for this challenging task. In particular, we leverage the estimated 3D human pose for more accurate inference of the object spatial layout and dynamics. We evaluate this approach on our dataset, demonstrating that human-object relations can significantly reduce the ambiguity of articulated object reconstructions from challenging real-world videos. Code and dataset are available at https://github.com/facebookresearch/d3d-hoi.

📄 PDF Abstract BibTeX arXiv:2108.08420

Code (2)

facebookresearch/d3d-hoi 공식 구현 pytorch
ChicyChen/my_d3d pytorch

Tasks

Human-Object Interaction DetectionObject

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