Papers › Understanding Indoor Scenes Using 3D Geometric Phrases

Understanding Indoor Scenes Using 3D Geometric Phrases

1 Jun 2013CVPR 2013 6archive 2025-07-28

Wongun Choi, Yu-Wei Chao, Caroline Pantofaru, Silvio Savarese

Visual scene understanding is a difficult problem interleaving object detection, geometric reasoning and scene classification. We present a hierarchical scene model for learning and reasoning about complex indoor scenes which is computationally tractable, can be learned from a reasonable amount of training data, and avoids oversimplification. At the core of this approach is the 3D Geometric Phrase Model which captures the semantic and geometric relationships between objects which frequently co-occur in the same 3D spatial configuration. Experiments show that this model effectively explains scene semantics, geometry and object groupings from a single image, while also improving individual object detections.

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Tasks

General Classification Object Object Detection Room Layout Estimation Scene Classification Scene Understanding object-detection

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Room Layout Estimation	SUN RGB-D	3DGP	IoU	19.2	#7 of 7	Archive leaderboard	report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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