With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual
(RGB) sensing has become available for widespread use. The complementary nature of the …

Higher dimensional data such as video and 3D are the leading edge of multimedia retrieval
and computer vision research. In this survey, we give a comprehensive overview and key …

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 …

We present a new descriptor for activity recognition from videos acquired by a depth sensor.
Previous descriptors mostly compute shape and motion features independently; thus, they …

3D object recognition in cluttered scenes is a rapidly growing research area. Based on the
used types of features, 3D object recognition methods can broadly be divided into two …

This paper presents a new framework for human activity recognition from video sequences
captured by a depth camera. We cluster hypersurface normals in a depth sequence to form …

We present a modality hallucination architecture for training an RGB object detection model
which incorporates depth side information at training time. Our convolutional hallucination …

In this paper, we present a technique that places 3D bounding boxes around objects in an
RGB-D scene. Our approach makes best use of the 2D information to quickly reduce the …

The goal of this work is to represent objects in an RGB-D scene with corresponding 3D
models from a library. We approach this problem by first detecting and segmenting object …

In this paper, we address the problems of contour detection, bottom-up grouping, object
detection and semantic segmentation on RGB-D data. We focus on the challenging setting …