Generation of High-Level Concepts in 3D Scene Graphs via Autoregressive Diffusion

arXiv:2608.28733 · cs.RO, cs.LG · Submitted 2026-08-28 · Read on arXiv

cs.RO, cs.LG

Submitted: 2026-08-28

Updated: 2026-10-05

Terminology

• Clustering — 11× in this paper · explained in 2 episodes
• Generative Model — 7× in this paper · explained in 2 episodes
• Wasserstein Distance — 4× in this paper · explained in 4 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Fused Gromov-Wasserstein — 2× in this paper
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Graph Isomorphism Network — 2× in this paper
• Graph Transformer — 2× in this paper
• Abstraction — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Deep Graph Generation — 1× in this paper
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Exposure Bias — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Graph Isomorphism Networks with Edges — 1× in this paper
• Italian Ministry of University and Research — 1× in this paper
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Maximum Mean Discrepancy — 1× in this paper
• Modular Components — 1× in this paper · explained in 2 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes

Sources

• S-Graphs+: Real-time Localization and Mapping leveraging Hierarchical Representations
• A Generalization of Transformer Networks to Graphs
• Situationally-aware Path Planning Exploiting 3D Scene Graphs
• Generation of Uncertainty-Aware High-Level Spatial Concepts in Factorized 3D Scene Graphs via Graph Neural Networks

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