  As a result of an increasingly automatized and digitized industry, processes
are becoming more complex. Augmented Reality has shown considerable potential
in assisting workers with complex tasks by enhancing user understanding and
experience with spatial information. However, the acceptance and integration of
AR into industrial processes is still limited due to the lack of established
methods and tedious integration efforts. Meanwhile, deep neural networks have
achieved remarkable results in computer vision tasks and bear great prospects
to enrich Augmented Reality applications . In this paper, we propose an
Augmented-Reality-based human assistance system to assist workers in complex
manual tasks where we incorporate deep neural networks for computer vision
tasks. More specifically, we combine Augmented Reality with object and action
detectors to make workflows more intuitive and flexible. To evaluate our system
in terms of user acceptance and efficiency, we conducted several user studies.
We found a significant reduction in time to task completion in untrained
workers and a decrease in error rate. Furthermore, we investigated the users
learning curve with our assistance system.
