2 citations · 4 across the 8 of their papers we have counts for
12 papers
Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia
Khanh Nguyen, Ali Furkan Biten, Andres Mafla +2
Humans exploit prior knowledge to describe images, and are able to adapt their explanation to specific contextual information, even to the extent of inventing plausible explanation…
MUST-VQA: MUltilingual Scene-text VQA
Emanuele Vivoli, Ali Furkan Biten, Andres Mafla +2
In this paper, we present a framework for Multilingual Scene Text Visual Question Answering that deals with new languages in a zero-shot fashion. Specifically, we consider the task…
Out-of-Vocabulary Challenge Report
Sergi Garcia-Bordils, Andrés Mafla, Ali Furkan Biten +5
This paper presents final results of the Out-Of-Vocabulary 2022 (OOV) challenge. The OOV contest introduces an important aspect that is not commonly studied by Optical Character Re…
Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement
Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla +6
In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text)…
Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching
Ali Furkan Biten, Andres Mafla, Lluis Gomez +1
The task of image-text matching aims to map representations from different modalities into a common joint visual-textual embedding. However, the most widely used datasets for this…
StacMR: Scene-Text Aware Cross-Modal Retrieval
Andrés Mafla, Rafael Sampaio de Rezende, Lluís Gómez +2
Recent models for cross-modal retrieval have benefited from an increasingly rich understanding of visual scenes, afforded by scene graphs and object interactions to mention a few.…
Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval
Andres Mafla, Sounak Dey, Ali Furkan Biten +2
Scene text instances found in natural images carry explicit semantic information that can provide important cues to solve a wide array of computer vision problems. In this paper, w…
Multimodal grid features and cell pointers for Scene Text Visual Question Answering
Lluís Gómez, Ali Furkan Biten, Rubèn Tito +4
This paper presents a new model for the task of scene text visual question answering, in which questions about a given image can only be answered by reading and understanding scene…
Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features
Andres Mafla, Sounak Dey, Ali Furkan Biten +2
Text contained in an image carries high-level semantics that can be exploited to achieve richer image understanding. In particular, the mere presence of text provides strong guidin…
ICDAR 2019 Competition on Scene Text Visual Question Answering
Ali Furkan Biten, Rubèn Tito, Andres Mafla +6
This paper presents final results of ICDAR 2019 Scene Text Visual Question Answering competition (ST-VQA). ST-VQA introduces an important aspect that is not addressed by any Visual…
Scene Text Visual Question Answering
Ali Furkan Biten, Ruben Tito, Andres Mafla +5
Current visual question answering datasets do not consider the rich semantic information conveyed by text within an image. In this work, we present a new dataset, ST-VQA, that aims…
Single Shot Scene Text Retrieval
Lluís Gómez, Andrés Mafla, Marçal Rusiñol +1
Textual information found in scene images provides high level semantic information about the image and its context and it can be leveraged for better scene understanding. In this p…