21 citations · 31 across the 4 of their papers we have counts for
8 papers
Location Sensitive Image Retrieval and Tagging
Raul Gomez, Jaume Gibert, Lluis Gomez +1
People from different parts of the globe describe objects and concepts in distinct manners. Visual appearance can thus vary across different geographic locations, which makes locat…
Extended Labeled Faces in-the-Wild (ELFW): Augmenting Classes for Face Segmentation
Rafael Redondo, Jaume Gibert
Existing face datasets often lack sufficient representation of occluding objects, which can hinder recognition, but also supply meaningful information to understand the visual cont…
Exploring Hate Speech Detection in Multimodal Publications
Raul Gomez, Jaume Gibert, Lluis Gomez +1
In this work we target the problem of hate speech detection in multimodal publications formed by a text and an image. We gather and annotate a large scale dataset from Twitter, MMH…
Selective Style Transfer for Text
Raul Gomez, Ali Furkan Biten, Lluis Gomez +3
This paper explores the possibilities of image style transfer applied to text maintaining the original transcriptions. Results on different text domains (scene text, machine printe…
AI in the media and creative industries
Giuseppe Amato, Malte Behrmann, Frédéric Bimbot +16
Thanks to the Big Data revolution and increasing computing capacities, Artificial Intelligence (AI) has made an impressive revival over the past few years and is now omnipresent in…
Self-Supervised Learning from Web Data for Multimodal Retrieval
Raul Gomez, Lluis Gomez, Jaume Gibert +1
Self-Supervised learning from multimodal image and text data allows deep neural networks to learn powerful features with no need of human annotated data. Web and Social Media platf…
Learning from #Barcelona Instagram data what Locals and Tourists post about its Neighbourhoods
Raul Gomez, Lluis Gomez, Jaume Gibert +1
Massive tourism is becoming a big problem for some cities, such as Barcelona, due to its concentration in some neighborhoods. In this work we gather Instagram data related to Barce…
Learning to Learn from Web Data through Deep Semantic Embeddings
Raul Gomez, Lluis Gomez, Jaume Gibert +1
In this paper we propose to learn a multimodal image and text embedding from Web and Social Media data, aiming to leverage the semantic knowledge learnt in the text domain and tran…