Efficient scene text detection with textual attention tower
Zhang, L., Liu, Y., Xiao, H., Yang, L., Zhu, G., Shah, S.A.A., Bennamoun, M. and Shen, P. (2020) Efficient scene text detection with textual attention tower. In: IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP) 2020, 4 - 8 May 2020, Barcelona, Spain
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Abstract
Scene text detection has received attention for years and achieved an impressive performance across various benchmarks. In this work, we propose an efficient and accurate approach to detect multi-oriented text in scene images. The proposed feature fusion mechanism allows us to use a shallower network to reduce the computational complexity. A self-attention mechanism is adopted to suppress false positive detections. Experiments on public benchmarks including ICDAR 2013, ICDAR 2015 and MSRA-TD500 show that our proposed approach can achieve better or comparable performances with fewer parameters and less computational cost.
Item Type: | Conference Paper |
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Murdoch Affiliation(s): | IT, Media and Communications |
URI: | http://researchrepository.murdoch.edu.au/id/eprint/59865 |
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