CVPR2017: Learning Deep Context-aware Features over Body and Latent Parts for
論文查看 作者是中科院的Dangwei Li等。這篇工作是multi-class person identification tasks，主要創新有三點：（1）用空洞卷積（dilated conv）進行多尺度特徵提取，減少傳統CNN提取特徵的信息損失；（2）利用Spatial Transformer Networks (STN，其中作者設置了三個參數限制) 提取可變的body-part，相比較於r
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相關文章
- 1. Learning Deep Features for Discriminative Localization
- 2. 《Learning Features and Parts for Fine-Grained Recognition》論文閱讀筆記
- 3. CVPR2017 tutorial: 3D Deep Learning
- 4. Comparison of SIFT Encoded and Deep Learning Features for the Classification and Detection of Esca D
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