Search Results for author: Minesh Mathew

Found 13 papers, 2 papers with code

Watching the News: Towards VideoQA Models that can Read

no code implementations10 Nov 2022 Soumya Jahagirdar, Minesh Mathew, Dimosthenis Karatzas, C. V. Jawahar

We demonstrate the limitations of current Scene Text VQA and VideoQA methods and propose ways to incorporate scene text information into VideoQA methods.

Question Answering Video Question Answering +2

An empirical study of CTC based models for OCR of Indian languages

no code implementations13 May 2022 Minesh Mathew, CV Jawahar

Recognition of text on word or line images, without the need for sub-word segmentation has become the mainstream of research and development of text recognition for Indian languages.

Optical Character Recognition Text Segmentation


no code implementations26 Apr 2021 Minesh Mathew, Viraj Bagal, Rubèn Pérez Tito, Dimosthenis Karatzas, Ernest Valveny, C. V Jawahar

Infographics are documents designed to effectively communicate information using a combination of textual, graphical and visual elements.

Question Answering Visual Question Answering +1

Benchmarking Scene Text Recognition in Devanagari, Telugu and Malayalam

no code implementations9 Apr 2021 Minesh Mathew, Mohit Jain, CV Jawahar

And the performance is bench-marked on a new IIIT-ILST dataset comprising of hundreds of real scene images containing text in the above mentioned scripts.

Scene Text Recognition

Document Visual Question Answering Challenge 2020

no code implementations20 Aug 2020 Minesh Mathew, Ruben Tito, Dimosthenis Karatzas, R. Manmatha, C. V. Jawahar

For the task 1 a new dataset is introduced comprising 50, 000 questions-answer(s) pairs defined over 12, 767 document images.

Question Answering Retrieval +1

RoadText-1K: Text Detection & Recognition Dataset for Driving Videos

no code implementations19 May 2020 Sangeeth Reddy, Minesh Mathew, Lluis Gomez, Marcal Rusinol, Dimosthenis Karatzas., C. V. Jawahar

State of the art methods for text detection, recognition and tracking are evaluated on the new dataset and the results signify the challenges in unconstrained driving videos compared to existing datasets.

ICDAR 2019 Competition on Scene Text Visual Question Answering

no code implementations30 Jun 2019 Ali Furkan Biten, Rubèn Tito, Andres Mafla, Lluis Gomez, Marçal Rusiñol, Minesh Mathew, C. V. Jawahar, Ernest Valveny, Dimosthenis Karatzas

ST-VQA introduces an important aspect that is not addressed by any Visual Question Answering system up to date, namely the incorporation of scene text to answer questions asked about an image.

Question Answering Visual Question Answering +1

Unconstrained Scene Text and Video Text Recognition for Arabic Script

no code implementations7 Nov 2017 Mohit Jain, Minesh Mathew, C. V. Jawahar

For scripts like Arabic, a major challenge in developing robust recognizers is the lack of large quantity of annotated data.

Scene Text Recognition

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