no code implementations • 15 Dec 2023 • Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
We employ a federated learning scheme, that reflects the real-life distribution of documents in different businesses, and we explore the use case where the ID of the invoice issuer is the sensitive information to be protected.
1 code implementation • 7 May 2023 • Lei Kang, Lichao Zhang, Dazhi Jiang
Speech Emotion Recognition (SER) is to recognize human emotions in a natural verbal interaction scenario with machines, which is considered as a challenging problem due to the ambiguous human emotions.
no code implementations • 12 Apr 2022 • Lei Kang, Pau Riba, Marçal Rusiñol, Alicia Fornés, Mauricio Villegas
Once properly trained, our method can also be adapted to new target data by only accessing unlabeled text-line images to mimic handwritten styles and produce images with any textual content.
no code implementations • 26 May 2020 • Lei Kang, Pau Riba, Marçal Rusiñol, Alicia Fornés, Mauricio Villegas
Sequential architectures are a perfect fit to model text lines, not only because of the inherent temporal aspect of text, but also to learn probability distributions over sequences of characters and words.
Ranked #8 on Handwritten Text Recognition on IAM
3 code implementations • ECCV 2020 • Lei Kang, Pau Riba, Yaxing Wang, Marçal Rusiñol, Alicia Fornés, Mauricio Villegas
We propose a novel method that is able to produce credible handwritten word images by conditioning the generative process with both calligraphic style features and textual content.
no code implementations • 21 Dec 2019 • Lei Kang, Pau Riba, Mauricio Villegas, Alicia Fornés, Marçal Rusiñol
The main challenge faced when training a language model is to deal with the language model corpus which is usually different to the one used for training the handwritten word recognition system.
no code implementations • 18 Sep 2019 • Lei Kang, Marçal Rusiñol, Alicia Fornés, Pau Riba, Mauricio Villegas
Handwritten Text Recognition (HTR) is still a challenging problem because it must deal with two important difficulties: the variability among writing styles, and the scarcity of labelled data.