3 citations · 11 across the 13 of their papers we have counts for
17 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)…
OCR-IDL: OCR Annotations for Industry Document Library Dataset
Ali Furkan Biten, Rubèn Tito, Lluis Gomez +2
Pretraining has proven successful in Document Intelligence tasks where deluge of documents are used to pretrain the models only later to be finetuned on downstream tasks. One of th…
LaTr: Layout-Aware Transformer for Scene-Text VQA
Ali Furkan Biten, Ron Litman, Yusheng Xie +2
We propose a novel multimodal architecture for Scene Text Visual Question Answering (STVQA), named Layout-Aware Transformer (LaTr). The task of STVQA requires models to reason over…
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…
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…
Localizing Infinity-shaped fishes: Sketch-guided object localization in the wild
Pau Riba, Sounak Dey, Ali Furkan Biten +1
This work investigates the problem of sketch-guided object localization (SGOL), where human sketches are used as queries to conduct the object localization in natural images. In th…
One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
Mohamed Ali Souibgui, Ali Furkan Biten, Sounak Dey +5
Low resource Handwritten Text Recognition (HTR) is a hard problem due to the scarce annotated data and the very limited linguistic information (dictionaries and language models). F…
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…
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…
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…
Good News, Everyone! Context driven entity-aware captioning for news images
Ali Furkan Biten, Lluis Gomez, Marçal Rusiñol +1
Current image captioning systems perform at a merely descriptive level, essentially enumerating the objects in the scene and their relations. Humans, on the contrary, interpret ima…