456 citations · 700 across the 23 of their papers we have counts for
9 papers · 1 filter
On Calibration of Scene-Text Recognition Models
Ron Slossberg, Oron Anschel, Amir Markovitz +6
In this work, we study the problem of word-level confidence calibration for scene-text recognition (STR). Although the topic of confidence calibration has been an active research a…
Sequence-to-Sequence Contrastive Learning for Text Recognition
Aviad Aberdam, Ron Litman, Shahar Tsiper +5
We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition. To account for the sequence-to-sequence…
A Comprehensive Study of Deep Video Action Recognition
Yi Zhu, Xinyu Li, Chunhui Liu +7
Video action recognition is one of the representative tasks for video understanding. Over the last decade, we have witnessed great advancements in video action recognition thanks t…
Document Visual Question Answering Challenge 2020
Minesh Mathew, Ruben Tito, Dimosthenis Karatzas +2
This paper presents results of Document Visual Question Answering Challenge organized as part of "Text and Documents in the Deep Learning Era" workshop, in CVPR 2020. The challenge…
DocVQA: A Dataset for VQA on Document Images
Minesh Mathew, Dimosthenis Karatzas, C. V. Jawahar
We present a new dataset for Visual Question Answering (VQA) on document images called DocVQA. The dataset consists of 50,000 questions defined on 12,000+ document images. Detailed…
Improving Semantic Segmentation via Self-Training
Yi Zhu, Zhongyue Zhang, Chongruo Wu +6
Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…