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Zhou_End-to-End_Wireframe_Parsing_ICCV_2019_paper.pdf
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🔗 Source: openaccess.thecvf.com
📊 Size: 6.91 MB
👤 Author: Yichao Zhou, Haozhi Qi, Yi Ma
⬇️ Downloads: 229

Summary

We present an end-to-end trainable algorithm to detect wireframes in an image, directly outputting a vectorized wireframe with semantically meaningful and geometrically salient junctions and lines. Our method, called L-CNN, outperforms previous state-of-the-art wireframe and line extraction algorithms. We also propose a new metric for wireframe evaluation that penalizes overlapped line segments and incorrect line connectivities. The L-CNN network consists of four parts: a feature extraction backbone, a junction proposal module, a line verification module, and a line sampling module, and can be trained end-to-end through back-propagation. Extensive experiments demonstrate the effectiveness of our approach.

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Description

We present an end-to-end trainable algorithm to detect wireframes in an image, directly outputting a vectorized wireframe with semantically meaningful and...

Technical Information

  • File Format: PDF
  • File Size: 6.91 MB
  • Pages: 10
  • Language: EN
  • Author: Yichao Zhou, Haozhi Qi, Yi Ma
  • Total Downloads: 229
  • Last Updated: 2 weeks ago

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