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Papers/Mask R-CNN with Pyramid Attention Network for Scene Text D...

Mask R-CNN with Pyramid Attention Network for Scene Text Detection

Zhida Huang, Zhuoyao Zhong, Lei Sun, Qiang Huo

2018-11-22Curved Text DetectionScene Text DetectionText Detection
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Abstract

In this paper, we present a new Mask R-CNN based text detection approach which can robustly detect multi-oriented and curved text from natural scene images in a unified manner. To enhance the feature representation ability of Mask R-CNN for text detection tasks, we propose to use the Pyramid Attention Network (PAN) as a new backbone network of Mask R-CNN. Experiments demonstrate that PAN can suppress false alarms caused by text-like backgrounds more effectively. Our proposed approach has achieved superior performance on both multi-oriented (ICDAR-2015, ICDAR-2017 MLT) and curved (SCUT-CTW1500) text detection benchmark tasks by only using single-scale and single-model testing.

Results

TaskDatasetMetricValueModel
Scene Text DetectionSCUT-CTW1500F-Measure85PAN
Scene Text DetectionSCUT-CTW1500FPS65.2PAN
Scene Text DetectionSCUT-CTW1500Precision86.8PAN
Scene Text DetectionSCUT-CTW1500Recall83.2PAN
Scene Text DetectionICDAR 2017 MLTPrecision80PAN
Scene Text DetectionICDAR 2017 MLTRecall69.8PAN
Scene Text DetectionICDAR 2015F-Measure85.9PAN
Scene Text DetectionICDAR 2015Precision90.8PAN
Scene Text DetectionICDAR 2015Recall81.5PAN

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