We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM
system that goes beyond traditional systems which output a purely geometric map of a static …

Inexpensive RGB-D cameras that give an RGB image together with depth data have
become widely available. In this paper, we use this data to build 3D point clouds of full …

Current 3D object detectors for autonomous driving are almost entirely trained on human-
annotated data. Although of high quality, the generation of such data is laborious and costly …

RGB-D cameras, which give an RGB image together with depths, are becoming increasingly
popular for robotic perception. In this paper, we address the task of detecting commonly …

We present a method for discovering object models from 3D meshes of indoor
environments. Our algorithm first decomposes the scene into a set of candidate mesh …

We present the hardware design, software architecture, and core algorithms of Herb 2.0, a
bimanual mobile manipulator developed at the Personal Robotics Lab at Carnegie Mellon …

For understanding the behavior, intent, and environment of a person, the surveillance
metaphor is traditional; that is, install cameras and observe the subject, and his/her …

Abstract Systems and methods are disclosed for classifying vehicles by performing scale
aware detection; performing detection assisted sampling for convolutional neural network …

We report on an extensive study of the benefits and limitations of current deep learning
approaches to object recognition in robot vision scenarios, introducing a novel dataset used …

We address the problem of understanding scenes from multiple sources of sensor data (eg,
a camera and a laser scanner) in the case where there is no one-to-one correspondence …