PUF replaces deterministic 2D-to-3D scene graph fusion with probabilistic node association and Dirichlet evidence accumulation, yielding substantial accuracy gains on 3DSSG and ReplicaSSG at 15ms/frame.
In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2representative citing papers
DeWorldSG improves 3D scene graph generation from RGB-D sequences by using depth-guided 3D Gaussian object nodes and V-JEPA 2 world-model priors for spatiotemporal relation refinement, reporting large recall gains on 3DSSG and ReplicaSSG.
citing papers explorer
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PUF: Plug-and-Play Uncertainty-Aware Fusion for Online 3D Scene Graph Generation
PUF replaces deterministic 2D-to-3D scene graph fusion with probabilistic node association and Dirichlet evidence accumulation, yielding substantial accuracy gains on 3DSSG and ReplicaSSG at 15ms/frame.
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DeWorldSG: Depth-Aware 3D Semantic Scene Graph Generation via World-Model Priors
DeWorldSG improves 3D scene graph generation from RGB-D sequences by using depth-guided 3D Gaussian object nodes and V-JEPA 2 world-model priors for spatiotemporal relation refinement, reporting large recall gains on 3DSSG and ReplicaSSG.