38 citations · 53 across the 3 of their papers we have counts for
4 papers · 1 filter
LocATe: End-to-end Localization of Actions in 3D with Transformers
Jiankai Sun, Bolei Zhou, Michael J. Black +1
Understanding a person's behavior from their 3D motion is a fundamental problem in computer vision with many applications. An important component of this problem is 3D Temporal Act…
BABEL: Bodies, Action and Behavior with English Labels
Abhinanda R. Punnakkal, Arjun Chandrasekaran, Nikos Athanasiou +2
Understanding the semantics of human movement -- the what, how and why of the movement -- is an important problem that requires datasets of human actions with semantic labels. Exis…
Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings
Viraj Prabhu, Arjun Chandrasekaran, Kate Saenko +1
Generalizing deep neural networks to new target domains is critical to their real-world utility. In practice, it may be feasible to get some target data labeled, but to be cost-eff…
A Computational Model of Early Word Learning from the Infant's Point of View
Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza +2
Human infants have the remarkable ability to learn the associations between object names and visual objects from inherently ambiguous experiences. Researchers in cognitive science…