In this paper, we present a method for single image three-dimensional (3-D) cuboid object
detection and multiview object simultaneous localization and map** in both static and …

Although RGB-D sensors have enabled major breakthroughs for several vision tasks, such
as 3D reconstruction, we have not attained the same level of success in high-level scene …

In this article, we tackle the problem of depth estimation from single monocular images.
Compared with depth estimation using multiple images such as stereo depth perception …

We consider the problem of depth estimation from a single monocular image in this work. It
is a challenging task as no reliable depth cues are available, eg, stereo correspondences …

Depth estimation from single monocular images is a key component in scene
understanding. Most existing algorithms formulate depth estimation as a regression problem …

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 …

We propose an algorithm to predict room layout from a single image that generalizes across
panoramas and perspective images, cuboid layouts and more general layouts (eg" L"-shape …

This paper proposes an efficient and effective scheme to applying the sliding window
approach popular in computer vision to 3D data. Specifically, the sparse nature of the …

Learning depth from a single image, as an important issue in scene understanding, has
attracted a lot of attention in the past decade. The accuracy of the depth estimation has been …

In this paper, we tackle the problem of estimating the depth of a scene from a single image.
This is a challenging task, since a single image on its own does not provide any depth cue …