The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and
accelerating the automation of long-horizon and hierarchical manipulation tasks. The …

We introduce HT-Step, a large-scale dataset containing temporal annotations of instructional
article steps in cooking videos. It includes 122k segment-level annotations over 20k narrated …

Although action recognition for procedural tasks has received notable attention, it has a
fundamental flaw in that no measure of success for actions is provided. This limits the …

In this article, we deal with the problem of predicting action progress in videos. We argue
that this is an extremely important task, since it can be valuable for a wide range of …

Procedural knowledge is crucial for understanding and performing concrete real-world
tasks. Yet, despite the importance of procedural knowledge, research into procedural …

Understanding complex hand actions, such as assembly tasks or kitchen activities, from
hand skeleton data is an important yet challenging task. In this paper, we analyze hand …

Predicting future human behavior is an increasingly popular topic in computer vision, driven
by the interest in applications such as autonomous vehicles, digital assistants and human …

This study introduces an innovative Temporal Action Detection (TAD) model that is
distinguished by its lightweight structure and capability for end-to-end training, delivering …

Forecasting human actions and motion trajectories address the problem of predicting what a
person is going to do next and how they will perform it. This is crucial in a wide range of …

Foreseeing the future is one of the key factors of intelligence. It involves understanding of the
past and current environment as well as decent experience of its possible dynamics. In this …