4 papers · 1 filter
GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling
Hritik Bansal, Po-Nien Kung, P. Jeffrey Brantingham +2
Multimodal event argument role labeling (EARL), a task that assigns a role for each event participant (object) in an image is a complex challenge. It requires reasoning over the en…
Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks
Luca Bertinetto, Romain Mueller, Konstantinos Tertikas +2
Deep neural networks have improved image classification dramatically over the past decade, but have done so by focusing on performance measures that treat all classes other than th…
Imagining the Unseen: Learning a Distribution over Incomplete Images with Dense Latent Trees
Sebastian Kaltwang, Sina Samangooei, John Redford +1
Images are composed as a hierarchy of object parts. We use this insight to create a generative graphical model that defines a hierarchical distribution over image parts. Typically,…
A Dataset for Lane Instance Segmentation in Urban Environments
Brook Roberts, Sebastian Kaltwang, Sina Samangooei +3
Autonomous vehicles require knowledge of the surrounding road layout, which can be predicted by state-of-the-art CNNs. This work addresses the current lack of data for determining…