SA3D-L: A lightweight model for 3D object segmentation using neural radiance fields

The Segment Anything Model (SAM) has recently made significant progress in object segmentation within 2D images. However, the task of segmenting objects in a 3D space remains a primary hurdle in computer vision. The neural radiance field (NeRF) utilizes a multilayer perceptron (MLP) to effectively l...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 623; S. 129420
Hauptverfasser:	Liu, Jian, Yu, Zhen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 28.03.2025
Schlagworte:	2D–3D segmentation Multi-layer perceptron (MLP) Neural radiation field (NeRF) Novel view synthesis Segment Anything Model (SAM) 2D–3D segmentation Multi-layer perceptron (MLP) Neural radiation field (NeRF) Segment Anything Model (SAM) Novel view synthesis
ISSN:	0925-2312
Online-Zugang:	Volltext
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