Geometric and Semantic Coupling for Interaction Understanding in 3D Scenes

arXiv:2609.25247 · cs.CV, cs.AI · Submitted 2026-09-21 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-21

Updated: 2026-09-27

Comments: Project page: https://hyokong.github.io/segment-snap-page/

Code: https://github.com/3dlg-hcvc/s2o

Project page: https://hyokong.github.io/segment-snap-page

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Decode — 19× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Additivity — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Instance Segmentation — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Fidelity — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Articulate3D: Holistic Understanding of 3D Scenes as Universal Scene Description
• Decoupled Weight Decay Regularization
• Tversky loss function for image segmentation using 3D fully convolutional deep networks
• Open-Vocabulary Functional 3D Scene Graphs for Real-World Indoor Spaces

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