{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:41:37Z","timestamp":1732041697596},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription. This hybrid architecture, although accurate, is complex and less efficient. In this study, we propose a Single Visual model for Scene Text recognition within the patch-wise image tokenization framework, which dispenses with the sequential modeling entirely. The method, termed SVTR, firstly decomposes an image text into small patches named character components. Afterward, hierarchical stages are recurrently carried out by component-level mixing, merging and\/or combining. Global and local mixing blocks are devised to perceive the inter-character and intra-character patterns, leading to a multi-grained character component perception. Thus, characters are recognized by a simple linear prediction. Experimental results on both English and Chinese scene text recognition tasks demonstrate the effectiveness of SVTR. SVTR-L (Large) achieves highly competitive accuracy in English and outperforms existing methods by a large margin in Chinese, while running faster. In addition, SVTR-T (Tiny) is an effective and much smaller model, which shows appealing speed at inference. The code is publicly available at https:\/\/github.com\/PaddlePaddle\/PaddleOCR.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/124","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"884-890","source":"Crossref","is-referenced-by-count":91,"title":["SVTR: Scene Text Recognition with a Single Visual Model"],"prefix":"10.24963","author":[{"given":"Yongkun","family":"Du","sequence":"first","affiliation":[{"name":"School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China"}]},{"given":"Zhineng","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Collaborative Innovation Center of Intelligent Visual Computing, School of Computer Science, Fudan University, China"}]},{"given":"Caiyan","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China"}]},{"given":"Xiaoting","family":"Yin","sequence":"additional","affiliation":[{"name":"Baidu Inc., China"}]},{"given":"Tianlun","family":"Zheng","sequence":"additional","affiliation":[{"name":"Shanghai Collaborative Innovation Center of Intelligent Visual Computing, School of Computer Science, Fudan University, China"}]},{"given":"Chenxia","family":"Li","sequence":"additional","affiliation":[{"name":"Baidu Inc., China"}]},{"given":"Yuning","family":"Du","sequence":"additional","affiliation":[{"name":"Baidu Inc., China"}]},{"given":"Yu-Gang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Shanghai Collaborative Innovation Center of Intelligent Visual Computing, School of Computer Science, Fudan University, China"}]}],"member":"10584","event":{"number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2022","name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","start":{"date-parts":[[2022,7,23]]},"theme":"Artificial Intelligence","location":"Vienna, Austria","end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:07:50Z","timestamp":1658142470000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/124"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/124","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}