Research map / Detection and segmentation / CNN features
Learning Attraction Field Representation for Robust Line Segment Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use a-trous Residual U-Net instead of U-Net (ablation) | attraction-field line segment detector · WireFrame | F-measure: 0.752 -> 0.773 | Helped |
| use a-trous Residual U-Net instead of U-Net (ablation) | attraction-field line segment detector · YorkUrban | F-measure: 0.639 -> 0.646 | Helped |
| use a-trous Residual U-Net instead of U-Net (ablation) | attraction-field line segment detector · WireFrame | FPS: 10.3 -> 6.6 | Hurt |
| predict attraction fields and apply the squeeze module rather than use the Wireframe parser | line segment detection · WireFrame | F-measure: 0.728 -> 0.773 | Helped |
| predict attraction fields and apply the squeeze module rather than use the Wireframe parser | line segment detection · YorkUrban | F-measure: 0.627 -> 0.646 | Helped |
Closest papers by meaning
- DeepLSD: Line Segment Detection and Refinement With Deep Image Gradients (CVPR 2023 · similarity 0.90)
- SOLD2: Self-Supervised Occlusion-Aware Line Description and Detection (CVPR 2021 · similarity 0.89)
- ScaleLSD: Scalable Deep Line Segment Detection Streamlined (CVPR 2025 · similarity 0.88)
- Improving Transformer Based Line Segment Detection with Matched Predicting and Re-ranking (AAAI 2025 · similarity 0.86)
- Integrating Low-Level Visual Cues for Enhanced Unsupervised Semantic Segmentation (AAAI 2025 · similarity 0.85)
- Learning Hierarchical Image Segmentation For Recognition and By Recognition (ICLR 2024 · similarity 0.84)
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