338 citations · 546 across the 47 of their papers we have counts for
59 papers
Understanding Video Scenes through Text: Insights from Text-based Video Question Answering
Soumya Jahagirdar, Minesh Mathew, Dimosthenis Karatzas +1
Researchers have extensively studied the field of vision and language, discovering that both visual and textual content is crucial for understanding scenes effectively. Particularl…
STEP -- Towards Structured Scene-Text Spotting
Sergi Garcia-Bordils, Dimosthenis Karatzas, Marçal Rusiñol
We introduce the structured scene-text spotting task, which requires a scene-text OCR system to spot text in the wild according to a query regular expression. Contrary to generic s…
Reading Between the Lanes: Text VideoQA on the Road
George Tom, Minesh Mathew, Sergi Garcia +2
Text and signs around roads provide crucial information for drivers, vital for safe navigation and situational awareness. Scene text recognition in motion is a challenging problem,…
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
ICDAR 2023 Video Text Reading Competition for Dense and Small Text
Weijia Wu, Yuzhong Zhao, Zhuang Li +5
Recently, video text detection, tracking, and recognition in natural scenes are becoming very popular in the computer vision community. However, most existing algorithms and benchm…
ICDAR 2023 Competition on Reading the Seal Title
Wenwen Yu, Mingyu Liu, Mingrui Chen +5
Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly f…
DocILE Benchmark for Document Information Localization and Extraction
Štěpán Šimsa, Milan Šulc, Michal Uřičář +8
This paper introduces the DocILE benchmark with the largest dataset of business documents for the tasks of Key Information Localization and Extraction and Line Item Recognition. It…
Hierarchical multimodal transformers for Multi-Page DocVQA
Rubèn Tito, Dimosthenis Karatzas, Ernest Valveny
Document Visual Question Answering (DocVQA) refers to the task of answering questions from document images. Existing work on DocVQA only considers single-page documents. However, i…
Watching the News: Towards VideoQA Models that can Read
Soumya Jahagirdar, Minesh Mathew, Dimosthenis Karatzas +1
Video Question Answering methods focus on commonsense reasoning and visual cognition of objects or persons and their interactions over time. Current VideoQA approaches ignore the t…
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…
ICDAR 2021 Competition on Document VisualQuestion Answering
Rubèn Tito, Minesh Mathew, C. V. Jawahar +2
In this report we present results of the ICDAR 2021 edition of the Document Visual Question Challenges. This edition complements the previous tasks on Single Document VQA and Docum…
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…
Asking questions on handwritten document collections
Minesh Mathew, Lluis Gomez, Dimosthenis Karatzas +1
This work addresses the problem of Question Answering (QA) on handwritten document collections. Unlike typical QA and Visual Question Answering (VQA) formulations where the answer…
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…
Document Collection Visual Question Answering
Rubèn Tito, Dimosthenis Karatzas, Ernest Valveny
Current tasks and methods in Document Understanding aims to process documents as single elements. However, documents are usually organized in collections (historical records, purch…
InfographicVQA
Minesh Mathew, Viraj Bagal, Rubèn Pérez Tito +3
Infographics are documents designed to effectively communicate information using a combination of textual, graphical and visual elements. In this work, we explore the automatic und…
ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction
Zheng Huang, Kai Chen, Jianhua He +4
Scanned receipts OCR and key information extraction (SROIE) represent the processeses of recognizing text from scanned receipts and extracting key texts from them and save the extr…
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…