Abstract
In the last years, solutions were proposed in the literature to alleviate the complexity of using sophisticated graphic suites for 3D scene generation by leveraging automatic tools. The most common approach based on the processing of text descriptions, however, may not represent the ideal solution, e.g., for fast prototyping purposes. This paper proposes an alternative methodology able to extract information about the objects and the layout of the scene to be created from a single 2D image. Compared to previous works, experimental results reported in this work show improvements in terms of similarity between the 2D and 3D scenes.
This work has been supported by VR@POLITO initiative.
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Notes
- 1.
Blender: https://www.blender.org/.
- 2.
Autodesk Maya: https://www.autodesk.com/products/maya/overview.
- 3.
Camera Calibration PVR: https://github.com/mrossini-ethz/camera-calibration-pvr.
- 4.
XiaohuLuVPDetection: https://github.com/rayryeng/XiaohuLuVPDetection.
- 5.
Image AI: https://github.com/OlafenwaMoses/ImageAI.
- 6.
COCO dataset: https://cocodataset.org/#home.
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Cannavò, A. et al. (2021). An Automatic 3D Scene Generation Pipeline Based on a Single 2D Image. In: De Paolis, L.T., Arpaia, P., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2021. Lecture Notes in Computer Science(), vol 12980. Springer, Cham. https://doi.org/10.1007/978-3-030-87595-4_9
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