Performing prescribed physical exercises during home-based rehabilitation programs plays
an important role in regaining muscle strength and improving balance for people with …

We target at the task of weakly-supervised action localization (WSAL), where only video-
level action labels are available during model training. Despite the recent progress, existing …

Procedural activity understanding requires perceiving human actions in terms of a broader
task, where multiple keysteps are performed in sequence across a long video to reach a …

In this paper we tackle the problem of self-supervised video alignment and activity progress
prediction using in-the-wild videos. Our proposed self-supervised representation learning …

Instructional videos are an important resource to learn procedural tasks from human
demonstrations. However, the instruction steps in such videos are typically short and sparse …

In this paper, we study the problem of procedure planning in instructional videos. Here, an
agent must produce a plausible sequence of actions that can transform the environment …

In this paper, we study the problem of procedure planning in instructional videos, which aims
to make goal-directed plans given the current visual observations in unstructured real-life …

In this paper, we propose Skip-Plan, a condensed action space learning method for
procedure planning in instructional videos. Current procedure planning methods all stick to …

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 …

In this paper we present an approach for localizing steps of procedural activities in narrated
how-to videos. To deal with the scarcity of labeled data at scale, we source the step …