Learning Attentive Pairwise Interaction for Fine-Grained Classification論文解讀
論文鏈接：https://arxiv.org/abs/2002.10191 分享的這篇文章來自於AAAI2020，文章的整個思路並不難理解。文章的idea來自於我們人類對相似圖像的識別。一般來說，我們識別相似的圖像，一方面是去找到圖像中特殊的區域來進行識別，另一方面是通過比較圖像對來有效地得到對比線索。這篇論文就是從後者獲得的靈感。 文章提出了Attentive Pairwise Interact
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相關文章
- 1. 論文閱讀筆記《Generative Adversarial Residual Pairwise Networks for One Shot Learning 》
- 2. AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
- 3. 論文閱讀筆記《Attentive Weights Generation for Few Shot Learning via Information Maximization》
- 4. 論文閱讀理解 - Learning Spatial Regularization for Multi-label Image Classification
- 5. CVPR 2017 Deep representation learning for human motion prediction and classification 論文解讀
- 6. CVPR2016(classification)：論文解讀《Deep Residual Learning for Image Recognition》
- 7. Pairwise Confusion for Fine-Grained Visual Classification
- 8. 論文閱讀：Action recognition for human-marionette interaction.
- 9. 論文學習4-An Attentive Neural Architecture for Fine-grained Entity Type Classification
- 10. 論文閱讀筆記 | (ECCV 2018) Learning to Navigate for Fine-grained Classification