[論文閱讀]Learning a Discriminative Feature Network for Semantic Segmentation
前言 Introduciton 作者提出了兩個在語義分割之中的問題: 類內矛盾 -> 有着不同外觀但是有相同標籤 類間矛盾 -> 有着相同的外觀但是有着不同標籤 所以作者提出了Smoonth NetWork去解決類內特徵不一致的問題,Border Network去解決分辨相鄰塊有相同外表但是標籤不同的問題。 同時考慮兩個決定性的因素: 多尺度的特徵圖和有全文信息的特徵圖 但多尺度的特徵圖的引入,對
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相關文章
- 1. 18-Learning-a-Discriminative-Feature-Network-for-Semantic-Segmentation
- 2. Learning a Discriminative Feature Network for Semantic Segmentation
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- 4. Learning a Discriminative Feature Network for Semantic Segmentation閱讀筆記
- 5. 【論文學習記錄】Learning a Discriminative Feature Network for Semantic Segmentation
- 6. 【論文閱讀】Learning Deconvolution Network for Semantic Segmentation
- 7. Learning a Discriminative Feature Network for Semantic Segmentation_CVPR2018
- 8. 語義分割--(DFN)Learning a Discriminative Feature Network for Semantic Segmentation
- 9. [ICCV2019論文閱讀]ACFNet: Attentional Class Feature Network for Semantic Segmentation
- 10. 【論文筆記】Learning Deconvolution Network for Semantic Segmentation