196 citations · 458 across the 30 of their papers we have counts for
6 papers · 1 filter
4D-Net for Learned Multi-Modal Alignment
AJ Piergiovanni, Vincent Casser, Michael S. Ryoo +1
We present 4D-Net, a 3D object detection approach, which utilizes 3D Point Cloud and RGB sensing information, both in time. We are able to incorporate the 4D information by perform…
Unsupervised Discovery of Actions in Instructional Videos
AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo +1
In this paper we address the problem of automatically discovering atomic actions in unsupervised manner from instructional videos. Instructional videos contain complex activities a…
Unsupervised Action Segmentation for Instructional Videos
AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo +1
In this paper we address the problem of automatically discovering atomic actions in unsupervised manner from instructional videos, which are rarely annotated with atomic actions. W…
TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?
Michael S. Ryoo, AJ Piergiovanni, Anurag Arnab +2
In this paper, we introduce a novel visual representation learning which relies on a handful of adaptively learned tokens, and which is applicable to both image and video understan…
Adaptive Intermediate Representations for Video Understanding
Juhana Kangaspunta, AJ Piergiovanni, Rico Jonschkowski +2
A common strategy to video understanding is to incorporate spatial and motion information by fusing features derived from RGB frames and optical flow. In this work, we introduce a…
Recognizing Actions in Videos from Unseen Viewpoints
AJ Piergiovanni, Michael S. Ryoo
Standard methods for video recognition use large CNNs designed to capture spatio-temporal data. However, training these models requires a large amount of labeled training data, con…