Handwritten Chinese Text Recognition
3 papers with code • 0 benchmarks • 2 datasets
Handwritten Chinese text recognition is the task of interpreting handwritten Chinese input, e.g., from images of documents or scans.
Benchmarks
These leaderboards are used to track progress in Handwritten Chinese Text Recognition
ICDAR 2013
CASIA-HWDB
Latest papers with no code
Recognition of Handwritten Chinese Text by Segmentation: A Segment-annotation-free Approach
A novel weakly supervised learning method is proposed to enable the network to be trained using only transcript annotations; thus, the expensive character segmentation annotations required by previous segmentation-based methods can be avoided.
Joint Architecture and Knowledge Distillation in CNN for Chinese Text Recognition
Finally, the knowledge distillation with multiple losses is adopted to improve performance of the compact CNN.
Parsimonious HMMs for Offline Handwritten Chinese Text Recognition
Recently, hidden Markov models (HMMs) have achieved promising results for offline handwritten Chinese text recognition.
Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences.
Fully Convolutional Recurrent Network for Handwritten Chinese Text Recognition
This paper proposes an end-to-end framework, namely fully convolutional recurrent network (FCRN) for handwritten Chinese text recognition (HCTR).
