I will give an overview of large-scale datasets in the last years, and in particular talk about our own experience putting together the Cityscapes dataset and the challenges involved. During the 2nd part of the tutorial I will discuss recent methods for semantic pixel-level and instance-level labelling followed by some practical tips and tricks based on Cityscapes results.

There are many manipulation problems in the field of factory and warehouse automation. We applied various machine vision techniques to the system in order to tackle those challenges. Last year, we competed in the Amazon Picking Challenge with the system we developed. In this tutorial, we will explain the machine vision system and algorithm.

1. 10 min: Trends on Factory Automation (FA)
2. 20 min: Case study: Cell production robot systems
3. 20 min: Machine vision algorithms for FA
4. 10 min: Break
5. 10 min: Trends on Warehouse Automation (WA)
6. 20 min: Case study: Picking robot systems
7. 10 min: Machine vision algorithm for WA
8. 10 min: Other applications
9. 10 min: Questions