3 papers
cs.CV2023
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…
cs.CV2022
BRACE: The Breakdancing Competition Dataset for Dance Motion Synthesis
Davide Moltisanti, Jinyi Wu, Bo Dai +1
Generative models for audio-conditioned dance motion synthesis map music features to dance movements. Models are trained to associate motion patterns to audio patterns, usually wit…
cs.CV2016
SEMBED: Semantic Embedding of Egocentric Action Videos
Michael Wray, Davide Moltisanti, Walterio Mayol-Cuevas +1
We present SEMBED, an approach for embedding an egocentric object interaction video in a semantic-visual graph to estimate the probability distribution over its potential semantic…