The increasing demand for edge devices highlights the necessity for modern technologies to be adaptable to general-purpose hardware. Specifically, in fields like augmented reality, virtual reality, and computer graphics, reconstructing 3D objects from sparse point clouds is highly computationally intensive, presenting challenges for execution on embedded devices. In previous works, the speed of 3D mesh generation has been prioritized with respect to preserving a high level of detail. Our focus in this work is to enhance the speed of the inference in order to get closer to real-time mesh generation.
Lightweight transformer occupancy networks for 3d virtual object reconstruction / Tonti, Claudia; Amerini, Irene. - (2025), pp. 408-414. (Intervento presentato al convegno 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2025 tenutosi a Porto ; Potogallo) [10.5220/0013377400003912].
Lightweight transformer occupancy networks for 3d virtual object reconstruction
Tonti, Claudia
Primo
Writing – Original Draft Preparation
;Amerini, Irene
Ultimo
Supervision
2025
Abstract
The increasing demand for edge devices highlights the necessity for modern technologies to be adaptable to general-purpose hardware. Specifically, in fields like augmented reality, virtual reality, and computer graphics, reconstructing 3D objects from sparse point clouds is highly computationally intensive, presenting challenges for execution on embedded devices. In previous works, the speed of 3D mesh generation has been prioritized with respect to preserving a high level of detail. Our focus in this work is to enhance the speed of the inference in order to get closer to real-time mesh generation.| File | Dimensione | Formato | |
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MelisTonti_Lightweight_2025.pdf
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Note: DOI 10.5220/0013377400003912
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