Year: 2025
Type: conference-paper
Abstract: This paper introduces a novel exemplar-based framework for reading Chinese texts in natural scene or document images. We present the Deep Exemplar-based Chinese Text Recognizer, which is structured to first identify candidate characters as exemplars from each text-line, and subsequently recognize them by retrieving analogous exemplars from a database. With text-line level annotations, we design the exemplar discovery network to simultaneously recognize texts and capture individual character positions in a weak-supervision manner. The exemplar retrieval module is then crafted to identify the most similar exemplar and propagate the corresponding character label. This enables us to effectively rectify the misrecognized characters and boost the performance of scene text recognition. Experiments on four scenarios of Chinese texts demonstrate the effectiveness of our proposed framework.
Institutions: Fudan University, East China Normal University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Fudan University
OpenAlex ID: W4409366336