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《DeepLab v1:semantic image segmentation with deep convolutional nets and fully connected CRFs》論文筆記
時間 2020-12-29
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1. 概述 導讀:文章指出僅僅使用DCNNs網絡的最後一層實現精確地語義分割是不足夠的。爲此,本篇文章的工作將DCNNs與概率圖模型來共同解決分割精度的問題。文章新提出的這個方法在定位分割的邊界上超過了之前的方法(當時),在VOC 2012數據集上取得了71.6%的IOU,GPU上速度爲8 FPS(不含CRF)。 相比於傳統的視覺算法(SIFT或HOG),DCNNs以其end-to-end方式獲得
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