Cycle Pixel Difference Network for Crisp Edge Detection Article Swipe

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Changsong Liu , Wei Zhang , Yanyan Liu , Mingyang Li , Wenlin Li , Yimeng Fan , Xiwei Bai , Liang Zhangd ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2409.04272

Edge detection, as a fundamental task in computer vision, has garnered increasing attention. The advent of deep learning has significantly advanced this field. However, recent deep learning-based methods generally face two significant issues: 1) reliance on large-scale pre-trained weights, and 2) generation of thick edges. We construct a U-shape encoder-decoder model named CPD-Net that successfully addresses these two issues simultaneously. In response to issue 1), we propose a novel cycle pixel difference convolution (CPDC), which effectively integrates edge prior knowledge with modern convolution operations, consequently successfully eliminating the dependence on large-scale pre-trained weights. As for issue 2), we construct a multi-scale information enhancement module (MSEM) and a dual residual connection-based (DRC) decoder to enhance the edge location ability of the model, thereby generating crisp and clean contour maps. Comprehensive experiments conducted on four standard benchmarks demonstrate that our method achieves competitive performance on the BSDS500 dataset (ODS=0.813 and AC=0.352), NYUD-V2 (ODS=0.760 and AC=0.223), BIPED dataset (ODS=0.898 and AC=0.426), and CID (ODS=0.59). Our approach provides a novel perspective for addressing these challenges in edge detection.

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Enhanced Data Rates For Gsm Evolution

Pixel

Computer Science

Artificial Intelligence

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Enhanced Data Rates for GSM Evolution Pixel Computer science Artificial intelligence

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2409.04272
PDF: https://arxiv.org/pdf/2409.04272
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4403587613

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OpenAlex ID: https://openalex.org/W4403587613

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DOI: https://doi.org/10.48550/arxiv.2409.04272

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Title: Cycle Pixel Difference Network for Crisp Edge Detection

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-09-06

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Authors: Changsong Liu, Wei Zhang, Yanyan Liu, Mingyang Li, Wenlin Li, Yimeng Fan, Xiwei Bai, Liang Zhangd

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Landing page: https://arxiv.org/abs/2409.04272

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PDF URL: https://arxiv.org/pdf/2409.04272

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Concepts: Enhanced Data Rates for GSM Evolution, Pixel, Computer science, Artificial intelligence

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Related works (count): 10

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