3D Scene Segmentation: A Comprehensive Survey and Open Problems

3D Scene Segmentation: A Comprehensive Survey and Open Problems

This paper presents a detailed review of recent advancements in 3D indoor scene segmentation driven by deep learning techniques. It provides an overview of existing segmentation models, examines various data representations, data collection methods, augmentation techniques, and available datasets. A...

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Bibliographic Details
Main Authors: Slavcho Neshev, Krasimir Tonchev, Agata Manolova, Vladimir Poulkov
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
3D indoor scene segmentation
deep learning
data acquisition
segmentation models
performance metrics
3D models
Online Access:https://ieeexplore.ieee.org/document/11050424/
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https://ieeexplore.ieee.org/document/11050424/

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