Person Re-identification with Deep Similarity-Guided Graph Neural Network 論文筆記
一、提出問題 行人重識別任務需要穩健地估計人物圖像之間的視覺相似性。然而，現有的人物識別模型主要是獨立地估計probe和gallery圖像的不同圖像對的相似性，而忽略了不同probe-gallery圖像對之間的關係信息，這就造成了一些困難樣本的相似性估計可能不準確。 二、論文貢獻 提出了一種新的相似性引導圖神經網絡（SGGNN）用於行人重識別，該模型可以進行端到端的訓練。與大多數利用後處理階段中樣
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相關文章
- 1. 論文筆記：KDD 2019 Heterogeneous Graph Neural Network
- 2. ECCV2018-Person Re-identification with Deep Similarity-Guided Graph Neural Network
- 3. 論文筆記：DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification
- 4. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 5. [論文筆記]TextBoxes A Fast Text Detector with a Single Deep Neural Network
- 6. 03論文筆記《ImageNet Classification with Deep Convolutional Neural Network》
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- 9. 論文閱讀筆記（一）——Deep Convolutional Neural Network with Independent
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