activity
20192022
most citedContent and Style Aware Generation of Text-line Images for Handwriting Recognition

64 citations · 88 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202264 cited

Content and Style Aware Generation of Text-line Images for Handwriting Recognition

Lei Kang, Pau Riba, Marçal Rusiñol +2

Handwritten Text Recognition has achieved an impressive performance in public benchmarks. However, due to the high inter- and intra-class variability between handwriting styles, su…

cs.CV202020 cited

Pay Attention to What You Read: Non-recurrent Handwritten Text-Line Recognition

Lei Kang, Pau Riba, Marçal Rusiñol +2

The advent of recurrent neural networks for handwriting recognition marked an important milestone reaching impressive recognition accuracies despite the great variability that we o…

cs.CV2020

GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images

Lei Kang, Pau Riba, Yaxing Wang +3

Although current image generation methods have reached impressive quality levels, they are still unable to produce plausible yet diverse images of handwritten words. On the contrar…

cs.CV20194 cited

Candidate Fusion: Integrating Language Modelling into a Sequence-to-Sequence Handwritten Word Recognition Architecture

Lei Kang, Pau Riba, Mauricio Villegas +2

Sequence-to-sequence models have recently become very popular for tackling handwritten word recognition problems. However, how to effectively integrate an external language model i…

cs.CV2019

Unsupervised Adaptation for Synthetic-to-Real Handwritten Word Recognition

Lei Kang, Marçal Rusiñol, Alicia Fornés +2

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 la…