978 citations · 4.5k across the 70 of their papers we have counts for
11 papers · 1 filter
Action Modifiers: Learning from Adverbs in Instructional Videos
Hazel Doughty, Ivan Laptev, Walterio Mayol-Cuevas +1
We present a method to learn a representation for adverbs from instructional videos using weak supervision from the accompanying narrations. Key to our method is the fact that the…
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Antoine Miech, Jean-Baptiste Alayrac, Lucas Smaira +3
Annotating videos is cumbersome, expensive and not scalable. Yet, many strong video models still rely on manually annotated data. With the recent introduction of the HowTo100M data…
Synthetic Humans for Action Recognition from Unseen Viewpoints
Gül Varol, Ivan Laptev, Cordelia Schmid +1
Although synthetic training data has been shown to be beneficial for tasks such as human pose estimation, its use for RGB human action recognition is relatively unexplored. Our goa…
Learning to combine primitive skills: A step towards versatile robotic manipulation
Robin Strudel, Alexander Pashevich, Igor Kalevatykh +3
Manipulation tasks such as preparing a meal or assembling furniture remain highly challenging for robotics and vision. Traditional task and motion planning (TAMP) methods can solve…
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac +3
Learning text-video embeddings usually requires a dataset of video clips with manually provided captions. However, such datasets are expensive and time consuming to create and ther…
Cross-task weakly supervised learning from instructional videos
Dimitri Zhukov, Jean-Baptiste Alayrac, Ramazan Gokberk Cinbis +3
In this paper we investigate learning visual models for the steps of ordinary tasks using weak supervision via instructional narrations and an ordered list of steps instead of stro…