[NIPS2018 筆記] Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
論文下載地址 Abstract: Zero-Shot Learning (ZSL) is achieved via aligning the semantic relationships between the global image feature vector and the corresponding class semantic descriptions. However, using
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相關文章
- 1. 《Stacked Cross Attention for Image-Text Matching》
- 2. Stacked Attention Networks for Image Question Answering閱讀筆記
- 3. A3M：Attribute-Aware Attention Model for Fine-grained Representation Learning
- 4. VQA1-2016-Stacked Attention Networks for Image Question Answering
- 5. Stacked Latent Attention for Multimodal Reasoning [CVPR 2018]
- 6. recurrent model for visual attention
- 7. 《A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term》筆記
- 8. 論文筆記：Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering
- 9. Mask-guided Contrastive Attention Model for Person Re-Identification學習筆記
- 10. [文獻筆記]An Unsupervised Neural Attention Model for Aspect Extraction -- Ruidan He et al.