activity
20162022
most citedAction2Vec: A Crossmodal Embedding Approach to Action Learning

42 citations · 135 across the 15 of their papers we have counts for

collaborators

26 papers

cs.LG2021

Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling

Yu-Ying Liu, Alexander Moreno, Maxwell A. Xu +7

The Continuous-Time Hidden Markov Model (CT-HMM) is an attractive approach to modeling disease progression due to its ability to describe noisy observations arriving irregularly in…

cs.CV2021

Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias

Stefan Stojanov, Anh Thai, James M. Rehg

It is widely accepted that reasoning about object shape is important for object recognition. However, the most powerful object recognition methods today do not explicitly make use…

cs.CV2020

4D Human Body Capture from Egocentric Video via 3D Scene Grounding

Miao Liu, Dexin Yang, Yan Zhang +3

We introduce a novel task of reconstructing a time series of second-person 3D human body meshes from monocular egocentric videos. The unique viewpoint and rapid embodied camera mot…

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…

stat.ME2020

A Robust Functional EM Algorithm for Incomplete Panel Count Data

Alexander Moreno, Zhenke Wu, Jamie Yap +5

Panel count data describes aggregated counts of recurrent events observed at discrete time points. To understand dynamics of health behaviors, the field of quantitative behavioral…

cs.CV2019

Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video

Miao Liu, Siyu Tang, Yin Li +1

We address the challenging task of anticipating human-object interaction in first person videos. Most existing methods ignore how the camera wearer interacts with the objects, or s…