850 citations · 1.7k across the 63 of their papers we have counts for
9 papers · 1 filter
ICDAR 2019 Robust Reading Challenge on Reading Chinese Text on Signboard
Xi Liu, Rui Zhang, Yongsheng Zhou +13
Chinese scene text reading is one of the most challenging problems in computer vision and has attracted great interest. Different from English text, Chinese has more than 6000 comm…
A Deep Learning Approach for Robust Corridor Following
Vishnu Sashank Dorbala, A. H. Abdul Hafez, C. V. Jawahar
For an autonomous corridor following task where the environment is continuously changing, several forms of environmental noise prevent an automated feature extraction procedure fro…
A Baseline Neural Machine Translation System for Indian Languages
Jerin Philip, Vinay P. Namboodiri, C. V. Jawahar
We present a simple, yet effective, Neural Machine Translation system for Indian languages. We demonstrate the feasibility for multiple language pairs, and establish a strong basel…
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…
A Cost Efficient Approach to Correct OCR Errors in Large Document Collections
Deepayan Das, Jerin Philip, Minesh Mathew +1
Word error rate of an ocr is often higher than its character error rate. This is especially true when ocrs are designed by recognizing characters. High word accuracies are critical…
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…
CVIT-MT Systems for WAT-2018
Jerin Philip, Vinay P. Namboodiri, C. V. Jawahar
This document describes the machine translation system used in the submissions of IIIT-Hyderabad CVIT-MT for the WAT-2018 English-Hindi translation task. Performance is evaluated o…
Self-Supervised Visual Representations for Cross-Modal Retrieval
Yash Patel, Lluis Gomez, Marçal Rusiñol +2
Cross-modal retrieval methods have been significantly improved in last years with the use of deep neural networks and large-scale annotated datasets such as ImageNet and Places. Ho…
Low-Cost Transfer Learning of Face Tasks
Thrupthi Ann John, Isha Dua, Vineeth N Balasubramanian +1
Do we know what the different filters of a face network represent? Can we use this filter information to train other tasks without transfer learning? For instance, can age, head po…