{"type":"ScholarlyArticle","title":"IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection","authors":[{"name":"Qiangpeng Yang","slug":"qiangpeng-yang","given":"Qiangpeng","family":"Yang","affiliation":"Alibaba Group"},{"name":"Mengli Cheng","slug":"mengli-cheng","given":"Mengli","family":"Cheng","affiliation":"Alibaba Group"},{"name":"Wenmeng Zhou","slug":"wenmeng-zhou","given":"Wenmeng","family":"Zhou","affiliation":"Alibaba Group"},{"name":"Yan Chen","slug":"yan-chen","given":"Yan","family":"Chen","affiliation":"Alibaba Group"},{"name":"Minghui Qiu","slug":"minghui-qiu","given":"Minghui","family":"Qiu","affiliation":"Alibaba Group"},{"name":"Wei Lin","slug":"wei-lin","given":"Wei","family":"Lin","affiliation":"Alibaba Group"}],"abstract":"Incidental scene text detection, especially for multi-oriented text regions, is one of the most challenging tasks in many computer vision applications.Different from the common object detection task, scene text often suffers from a large variance of aspect ratio, scale, and orientation. To solve this problem, we propose a novel end-to-end scene text detector IncepText from an instance-aware segmentation perspective. We design a novel Inception-Text module and introduce deformable PSROI pooling to deal with multi-oriented text detection. Extensive experiments on ICDAR2015, RCTW-17, and MSRA-TD500 datasets demonstrate our method's superiority in terms of both effectiveness and efficiency. Our proposed method achieves 1st place result on ICDAR2015 challenge and the state-of-the-art performance on other datasets. Moreover, we have released our implementation as an OCR product which is available for public access.","doi":"10.24963/ijcai.2018/149","url":"https://ijcai.org/proceedings/2018/149","pdf":"https://ijcai.org/proceedings/2018/0149.pdf","markdown":"https://ijcai.org/proceedings/2018/149.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/149","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Computer Vision","track":"Main track","number":149,"pages":{"first":1071,"last":1077},"keywords":["Computer Vision: Recognition: Detection, Categorization, Indexing, Matching, Retrieval, Semantic Interpretation","Computer Vision: Computer Vision"],"videos":[],"references":[{"position":1,"raw":"[Busta et al., 2015] Michal Busta, Lukas Neumann, and Jiri Matas. 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