This article provides a comprehensive survey on pioneer and state-of-the-art 3D scene
geometry estimation methodologies based on single, two, or multiple images captured …

Recent deep networks that directly handle points in a point set, eg, PointNet, have been
state-of-the-art for supervised learning tasks on point clouds such as classification and …

We present an approach to interpret the major surfaces, objects, and support relations of an
indoor scene from an RGBD image. Most existing work ignores physical interactions or is …

Scene categorization is a fundamental problem in computer vision. However, scene
understanding research has been constrained by the limited scope of currently-used …

Progress in scene understanding requires reasoning about the rich and diverse visual
environments that make up our daily experience. To this end, we propose the Scene …

In this paper, we present a novel probabilistic generative model for multi-object traffic scene
understanding from movable platforms which reasons jointly about the 3D scene layout as …

This book is intended to give students at the advanced undergraduate or introduc tory
graduate level, and researchers in computer vision, robotics and computer graphics, a self …

We introduce an approach that leverages surface normal predictions, along with
appearance cues, to retrieve 3D models for objects depicted in 2D still images from a large …

This paper provides a comprehensive overview of urban reconstruction. While there exists a
considerable body of literature, this topic is still under active research. The work reviewed in …

Estimating geographic information from an image is an excellent, difficult high-level
computer vision problem whose time has come. The emergence of vast amounts of …