activity
20182022
most citedAction2Vec: A Crossmodal Embedding Approach to Action Learning

42 citations · 50 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20217 cited

No RL, No Simulation: Learning to Navigate without Navigating

Meera Hahn, Devendra Chaplot, Shubham Tulsiani +3

Most prior methods for learning navigation policies require access to simulation environments, as they need online policy interaction and rely on ground-truth maps for rewards. How…

cs.CV2020

Where Are You? Localization from Embodied Dialog

Meera Hahn, Jacob Krantz, Dhruv Batra +4

We present Where Are You? (WAY), a dataset of ~6k dialogs in which two humans -- an Observer and a Locator -- complete a cooperative localization task. The Observer is spawned at r…

cs.CV2019

Tripping through time: Efficient Localization of Activities in Videos

Meera Hahn, Asim Kadav, James M. Rehg +1

Localizing moments in untrimmed videos via language queries is a new and interesting task that requires the ability to accurately ground language into video. Previous works have ap…

cs.CV201942 cited

Action2Vec: A Crossmodal Embedding Approach to Action Learning

Meera Hahn, Andrew Silva, James M. Rehg

We describe a novel cross-modal embedding space for actions, named Action2Vec, which combines linguistic cues from class labels with spatio-temporal features derived from video cli…

cs.CV2018

Learning to Localize and Align Fine-Grained Actions to Sparse Instructions

Meera Hahn, Nataniel Ruiz, Jean-Baptiste Alayrac +2

Automatic generation of textual video descriptions that are time-aligned with video content is a long-standing goal in computer vision. The task is challenging due to the difficult…