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2010 NIPS NeurIPS 2010

Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces

Abstract

There has been a recent push in extraction of 3D spatial layout of scenes. However, none of these approaches model the 3D interaction between objects and the spatial layout. In this paper, we argue for a parametric representation of objects in 3D, which allows us to incorporate volumetric constraints of the physical world. We show that augmenting current structured prediction techniques with volumetric reasoning significantly improves the performance of the state-of-the-art.

📈 Trend Setter — 3D Vision
🧭 Keyword Pioneer — 3d scene understanding
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
🌱 Topic Pioneer — 3D Vision
🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning
🐣 Hot Topic Early Bird — structured prediction

Authors

Abhinav Gupta , Martial Hebert , Takeo Kanade , David M. Blei

Topics

Computer Vision > Analysis > 3D Vision Computer Vision > Analysis > Scene Understanding Computer Vision > Analysis > Semantic Segmentation Machine Learning > Core Methods > Structured Prediction Computer Vision > Processing > 3D Vision

Keywords

structured prediction scene understanding object detection 3d vision 3d scene understanding spatial layout estimation volumetric reasoning object-surface interaction 3d spatial layout object surfaces
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