activity
20162021
most citedImproving Text Proposals for Scene Images with Fully Convolutional Networks

20 citations · 38 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning

Ali Furkan Biten, Lluis Gomez, Dimosthenis Karatzas

Explaining an image with missing or non-existent objects is known as object bias (hallucination) in image captioning. This behaviour is quite common in the state-of-the-art caption…

cs.CV2018

TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces

Yash Patel, Lluis Gomez, Raul Gomez +3

The immense success of deep learning based methods in computer vision heavily relies on large scale training datasets. These richly annotated datasets help the network learn discri…

cs.CV201718 cited

Self-supervised learning of visual features through embedding images into text topic spaces

Lluis Gomez, Yash Patel, Marçal Rusiñol +2

End-to-end training from scratch of current deep architectures for new computer vision problems would require Imagenet-scale datasets, and this is not always possible. In this pape…

cs.CV201720 cited

Improving Text Proposals for Scene Images with Fully Convolutional Networks

Dena Bazazian, Raul Gomez, Anguelos Nicolaou +3

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. Combin…

cs.CV2016

A fine-grained approach to scene text script identification

Lluis Gomez, Dimosthenis Karatzas

This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condi…