978 citations · 4.5k across the 70 of their papers we have counts for
9 papers · 1 filter
Just Ask: Learning to Answer Questions from Millions of Narrated Videos
Antoine Yang, Antoine Miech, Josef Sivic +2
Recent methods for visual question answering rely on large-scale annotated datasets. Manual annotation of questions and answers for videos, however, is tedious, expensive and preve…
Learning Object Manipulation Skills via Approximate State Estimation from Real Videos
Vladimír Petrík, Makarand Tapaswi, Ivan Laptev +1
Humans are adept at learning new tasks by watching a few instructional videos. On the other hand, robots that learn new actions either require a lot of effort through trial and err…
RareAct: A video dataset of unusual interactions
Antoine Miech, Jean-Baptiste Alayrac, Ivan Laptev +2
This paper introduces a manually annotated video dataset of unusual actions, namely RareAct, including actions such as "blend phone", "cut keyboard" and "microwave shoes". RareAct…
The End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)
Samuel Albanie, Yang Liu, Arsha Nagrani +18
We present a new video understanding pentathlon challenge, an open competition held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020.…
Learning Obstacle Representations for Neural Motion Planning
Robin Strudel, Ricardo Garcia, Justin Carpentier +3
Motion planning and obstacle avoidance is a key challenge in robotics applications. While previous work succeeds to provide excellent solutions for known environments, sensor-based…
Occlusion resistant learning of intuitive physics from videos
Ronan Riochet, Josef Sivic, Ivan Laptev +1
To reach human performance on complex tasks, a key ability for artificial systems is to understand physical interactions between objects, and predict future outcomes of a situation…