activity
20172022
most citedMulti-label Music Genre Classification from Audio, Text, and Images Using Deep Features

64 citations · 80 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2022

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

Ligong Han, Jian Ren, Hsin-Ying Lee +5

Most methods for conditional video synthesis use a single modality as the condition. This comes with major limitations. For example, it is problematic for a model conditioned on an…

cs.CL2019

Learning Cross-lingual Embeddings from Twitter via Distant Supervision

Jose Camacho-Collados, Yerai Doval, Eugenio Martínez-Cámara +3

Cross-lingual embeddings represent the meaning of words from different languages in the same vector space. Recent work has shown that it is possible to construct such representatio…

cs.CL2018

Exploring Emoji Usage and Prediction Through a Temporal Variation Lens

Francesco Barbieri, Luis Marujo, Pradeep Karuturi +2

The frequent use of Emojis on social media platforms has created a new form of multimodal social interaction. Developing methods for the study and representation of emoji semantics…

cs.CL2018

Multimodal Emoji Prediction

Francesco Barbieri, Miguel Ballesteros, Francesco Ronzano +1

Emojis are small images that are commonly included in social media text messages. The combination of visual and textual content in the same message builds up a modern way of commun…

cs.IR201764 cited

Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features

Sergio Oramas, Oriol Nieto, Francesco Barbieri +1

Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focus…

cs.CL201716 cited

Are Emojis Predictable?

Francesco Barbieri, Miguel Ballesteros, Horacio Saggion

Emojis are ideograms which are naturally combined with plain text to visually complement or condense the meaning of a message. Despite being widely used in social media, their unde…