TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding

Scene graphs have proven to be highly effective for various scene understanding tasks due to their compact and explicit representation of relational information. However, current methods often overlook the critical importance of preserving symmetry when generating scene graphs from 3D point clouds,...

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Veröffentlicht in:	arXiv.org 2024-11
Hauptverfasser:	Pham, Quang P M, Nguyen, Khoi T N, Ngo, Lan C, Song, Dezhen, Do, Truong, Truong, Son Hy
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computer vision Graph matching Graph neural networks Graphical representations Graphs Neural networks Real time Robotics Robustness (mathematics) Scene analysis Source code Symmetry Three dimensional models Time dependence
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