With the availability of low-cost and compact 2.5/3D visual sensing devices, computer vision
community is experiencing a growing interest in visual scene understanding of indoor …

In this paper we study the problem of object detection for RGB-D images using semantically
rich image and depth features. We propose a new geocentric embedding for depth images …

In this paper, we address the 3D object detection task by capturing multi-level contextual
information with the self-attention mechanism and multi-scale feature fusion. Most existing …

We propose a viewpoint invariant model for 3D human pose estimation from a single depth
image. To achieve this, our discriminative model embeds local regions into a learned …

We present a real-time object-based SLAM system that leverages the largest object
database to date. Our approach comprises two main components:(1) a monocular SLAM …

We present a unified occlusion model for object instance detection under arbitrary viewpoint.
Whereas previous approaches primarily modeled local coherency of occlusions or …

Learning and predicting the pose parameters of a 3D hand model given an image, such as
locations of hand joints, is challenging due to large viewpoint changes and articulations, and …

Action analysis in image and video has been attracting more and more attention in computer
vision. Recognizing specific actions in video clips has been the main focus. We move in a …

In this paper we present Latent-Class Hough Forests, a method for object detection and 6
DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art …

In this paper we propose a method for the localization of multiple facial features on
challenging face images. In the regression forests (RF) framework, observations (patches) …