As robotic systems increasingly encounter complex and unconstrained
real...
Tracking an object's 6D pose, while either the object itself or the obse...
Object pose estimation is a core perception task that enables, for examp...
Object pose estimation is important for object manipulation and scene
un...
Object pose estimation is a non-trivial task that enables robotic
manipu...
Transparent objects are common in day-to-day life and hence find many
ap...
State-of-the-art object pose estimation handles multiple instances in a ...
This paper presents BURG-Toolkit, a set of open-source tools for Benchma...
Observational noise, inaccurate segmentation and ambiguity due to symmet...
Motion and dynamic environments, especially under challenging lighting
c...
Synthetic data generation has become essential in last years for feeding...
Assistive multi-armed bandit problems can be used to model team situatio...
Point cloud registration is a common step in many 3D computer vision tas...
While object semantic understanding is essential for most service roboti...
Object pose estimation enables robots to understand and interact with th...
Recent methods for 6D pose estimation of objects assume either textured ...
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-...
This paper presents the perception system of a new professional cleaning...
This article presents a method for grasping novel objects by learning fr...
Object classification with 3D data is an essential component of any scen...
Precise object pose estimation for robotics applications and augmented
r...
Estimating the 6D pose of objects using only RGB images remains challeng...
Developing robot perception systems for recognizing objects in the real-...
Providing machines with the ability to recognize objects like humans has...
The research in dense online 3D mapping is mostly focused on the geometr...
The ability to recognize objects is an essential skill for a robotic sys...
In this work we show that the classification performance of high-dimensi...
In this paper, we propose an efficient semantic segmentation framework f...