NIPS 2019 Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
文章目錄 Motivation Method Experiment 問題 參考 Motivation 細粒度識別問題 比普通的分類更難 很難收集數據：需要專家標註 需要小樣本學習 **是否可以生成更多的數據？**現有的最好的GANS如何？挑戰 GAN訓練需要許多的數據。可否降低訓練的數據量？或者換一種訓練方式？ Idea：微調 ImageNet上訓練的GANS。 Method Fine-tune
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相關文章
- 1. CNN for Visual Recognition (assignment1_Q1)
- 2. CNN for Visual Recognition (02)
- 3. CNN for Visual Recognition (01)
- 4. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 5. CS231n Convolutional Neural Networks for Visual Recognition
- 6. 數據合成方法 ： 論文 Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
- 7. nips 208 visual question answering 導讀
- 8. NIPS 2019 Transductive Zero-Shot Learning with Visual Structure Constraint
- 9. Convolutional Neural Networks for Visual Recognition
- 10. [Synthetic-data-with-text-and-image]