4.2k citations · 4.8k across the 11 of their papers we have counts for
13 papers
The Limits and Potentials of Deep Learning for Robotics
Niko Sünderhauf, Oliver Brock, Walter Scheirer +8
The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and machine learning com…
Multi-Modal Trip Hazard Affordance Detection On Construction Sites
Sean McMahon, Niko Sünderhauf, Ben Upcroft +1
Trip hazards are a significant contributor to accidents on construction and manufacturing sites, where over a third of Australian workplace injuries occur [1]. Current safety inspe…
Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting - Combined Colour and 3D Information
Inkyu Sa, Chris Lehnert, Andrew English +4
This paper presents a 3D visual detection method for the challenging task of detecting peduncles of sweet peppers (Capsicum annuum) in the field. Cutting the peduncle cleanly is on…
Deep Learning Features at Scale for Visual Place Recognition
Zetao Chen, Adam Jacobson, Niko Sunderhauf +5
The success of deep learning techniques in the computer vision domain has triggered a range of initial investigations into their utility for visual place recognition, all using gen…
Action Recognition: From Static Datasets to Moving Robots
Fahimeh Rezazadegan, Sareh Shirazi, Ben Upcroft +1
Deep learning models have achieved state-of-the- art performance in recognizing human activities, but often rely on utilizing background cues present in typical computer vision dat…
The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research
Jürgen Leitner, Adam W. Tow, Jake E. Dean +15
Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA Challenges are an established and important way to drive scientific progress. They make research comparable…