10 citations · 26 across the 16 of their papers we have counts for
8 papers · 1 filter
Learning Action Changes by Measuring Verb-Adverb Textual Relationships
Davide Moltisanti, Frank Keller, Hakan Bilen +1
The goal of this work is to understand the way actions are performed in videos. That is, given a video, we aim to predict an adverb indicating a modification applied to the action…
Who are you referring to? Coreference resolution in image narrations
Arushi Goel, Basura Fernando, Frank Keller +1
Coreference resolution aims to identify words and phrases which refer to same entity in a text, a core task in natural language processing. In this paper, we extend this task to re…
A Closer Look at Temporal Ordering in the Segmentation of Instructional Videos
Anil Batra, Shreyank N Gowda, Frank Keller +1
Understanding the steps required to perform a task is an important skill for AI systems. Learning these steps from instructional videos involves two subproblems: (i) identifying th…
Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition
Shreyank N Gowda, Marcus Rohrbach, Frank Keller +1
We address the problem of data augmentation for video action recognition. Standard augmentation strategies in video are hand-designed and sample the space of possible augmented dat…
Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation
Arushi Goel, Basura Fernando, Frank Keller +1
Scene graph generation (SGG) aims to capture a wide variety of interactions between pairs of objects, which is essential for full scene understanding. Existing SGG methods trained…
Finding the Right Moment: Human-Assisted Trailer Creation via Task Composition
Pinelopi Papalampidi, Frank Keller, Mirella Lapata
Movie trailers perform multiple functions: they introduce viewers to the story, convey the mood and artistic style of the film, and encourage audiences to see the movie. These dive…
A New Split for Evaluating True Zero-Shot Action Recognition
Shreyank N Gowda, Laura Sevilla-Lara, Kiyoon Kim +2
Zero-shot action recognition is the task of classifying action categories that are not available in the training set. In this setting, the standard evaluation protocol is to use ex…
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
Shreyank N Gowda, Laura Sevilla-Lara, Frank Keller +1
Zero-shot action recognition is the task of recognizingaction classes without visual examples, only with a seman-tic embedding which relates unseen to seen classes. Theproblem can…