Spatial computing

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Space-Mate: A 303.5-mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing

Space-Mate: A 303.5-mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing 150 150
Author(s): Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo

Abstract:

Simultaneous localization and mapping (SLAM) provides crucial ego-pose information and 3-D maps of the user environment, which are fundamental to emerging mobile spatial computing devices. Dense 3-D mapping and accurate pose estimation are particularly necessary for applications like augmented reality (AR) and autonomous navigation. However, existing SLAM processors are typically …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3610931
Publisher: IEEE

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IRIS: An Energy-Efficient Spatial Computing SoC for Real-Time Interactive Rendering and Modeling With Surface-Aware 3-D Gaussian Splatting

IRIS: An Energy-Efficient Spatial Computing SoC for Real-Time Interactive Rendering and Modeling With Surface-Aware 3-D Gaussian Splatting 150 150
Author(s): Seokchan Song, Seryeong Kim, Wonhoon Park, Jongjun Park, Sanghyuk An, Gwangtae Park, Minseo Kim, Hoi-Jun Yoo

Abstract:

The 3-D Gaussian splatting (3DGS), based on a machine learning-driven radiance field technique, is rapidly emerging as a next-generation solution in 3-D graphics. Owing to its short modeling time, computational simplicity, and high rendering quality, it is expected to replace traditional 3-D graphics on edge devices. However, its substantial memory …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 14
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3613707
Publisher: IEEE

View on IEEE Xplore

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