Re-ID：AlignedReID: Surpassing Human-Level Performance in Person Re-Identification 論文解析
剛讀完這篇文章，賊6，用動態規劃求最小路徑進行特徵對齊，很新奇，而且準確率很高。 下面是我對這篇論文的一個整理~ 這篇文章作者提出了AlignedReID的方法，其亮點在於：在數據集Market1501與CUHK03上，該方法實現的rank-1 accuracy 首超人類， 作者認爲： Traditional approaches have focused on low-level feature
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相關文章
- 1. 《AlignedReID: Surpassing Human-Level Performance in Person Re-Identification》論文解讀
- 2. AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
- 3. [論文閱讀]AlignedReID: Surpassing Human-Level Performance in Person Re-dentification
- 4. 【Person Re-ID】AlignedReID: Surpassing Human-Level Performance in Person Re-Identification
- 5. alignedReID: surpassing human-level performance in person re-identification (paper reading)
- 6. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 7. Surpassing Human-Level Performance on ImageNet Classification ImageNet Classification
- 8. SYSU-MM01的多模態Re-ID數據集 異構Heterogeneous person reidentification
- 9. part-aligned系列論文：1707.Deeply-Learned Part-Aligned Representations for Person Re-Identification 論文筆記
- 10. part-aligned系列論文：1707.ICCV.Pedestrian Alignment Network for Large-scale Person Re-identification 論文