Search Results for author:
Found 9 papers, 8 papers with code
Retrieval Guided Unsupervised Multi-domain Image-to-Image Translation
In this paper we propose the use of an image retrieval system to assist the image-to-image translation task.
Location Sensitive Image Retrieval and Tagging
People from different parts of the globe describe objects and concepts in distinct manners.
Exploring Hate Speech Detection in Multimodal Publications
In this work we target the problem of hate speech detection in multimodal publications formed by a text and an image.
Selective Style Transfer for Text
This paper explores the possibilities of image style transfer applied to text maintaining the original transcriptions.
Self-Supervised Learning from Web Data for Multimodal Retrieval
In this work we propose to exploit this free available data to learn a multimodal image and text embedding, aiming to leverage the semantic knowledge learnt in the text domain and transfer it to a visual model for semantic image retrieval.
Learning to Learn from Web Data through Deep Semantic Embeddings
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 transfer it to a visual model for semantic image retrieval.
Learning from #Barcelona Instagram data what Locals and Tourists post about its Neighbourhoods
We perform a language separate treatment of the data and show that it can be extrapolated to a tourists and locals separate analysis, and that tourism is reflected in Social Media at a neighborhood level.
TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces
We show that adequate visual features can be learned efficiently by training a CNN to predict the semantic textual context in which a particular image is more probable to appear as an illustration.
Improving Text Proposals for Scene Images with Fully Convolutional Networks
Text Proposals have emerged as a class-dependent version of object proposals - efficient approaches to reduce the search space of possible text object locations in an image.
