Artistic-style text detector and a new Movie-Poster dataset
Aoxiang Ning, Yiting Wei, Minglong Xue, Senming Zhong

TL;DR
This paper introduces a novel artistic-style text detection method utilizing Criss-Cross Attention and residual dense blocks, along with a new Movie-Poster dataset, to improve detection accuracy in complex artistic scenarios.
Contribution
The paper presents a new detection framework combining feature enhancement and boundary discrimination, and provides a specialized dataset for artistic-style text in movie posters.
Findings
Superior performance on the Movie-Poster dataset
Effective suppression of background noise in feature fusion
Accurate boundary proposal generation in artistic text detection
Abstract
Although current text detection algorithms demonstrate effectiveness in general scenarios, their performance declines when confronted with artistic-style text featuring complex structures. This paper proposes a method that utilizes Criss-Cross Attention and residual dense block to address the incomplete and misdiagnosis of artistic-style text detection by current algorithms. Specifically, our method mainly consists of a feature extraction backbone, a feature enhancement network, a multi-scale feature fusion module, and a boundary discrimination module. The feature enhancement network significantly enhances the model's perceptual capabilities in complex environments by fusing horizontal and vertical contextual information, allowing it to capture detailed features overlooked in artistic-style text. We incorporate residual dense block into the Feature Pyramid Network to suppress the effect…
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Taxonomy
TopicsVideo Analysis and Summarization · Generative Adversarial Networks and Image Synthesis · Music and Audio Processing
Methods*Communicated@Fast*How Do I Communicate to Expedia? · Softmax · Attention Is All You Need · Batch Normalization · Concatenated Skip Connection · Convolution · Dense Block
