1 code implementation • 29 Apr 2024 • Lei Kang, Mohamed Ali Souibgui, Fei Yang, Lluis Gomez, Ernest Valveny, Dimosthenis Karatzas
In our research, we explore machine unlearning for document classification problems, representing, to the best of our knowledge, the first investigation into this area.
1 code implementation • 29 Apr 2024 • Lei Kang, Rubèn Tito, Ernest Valveny, Dimosthenis Karatzas
In particular, we employ a visual-only document representation, leveraging the encoder from a document understanding model, Pix2Struct.
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.