Learning Visual Question Answering by Bootstrapping Hard Attention
Google DeepMind ECCV-2018
2018-08-05 19:24:44
Paper：https://arxiv.org/abs/1808.00300
Introduction：
本文尝试仅仅用 hard attention 的方法来抠出最有用的 feature，进行 VQA 任务的学习。
Soft Attention：
Existing attention models [7,8,9,10] are predominantly based on soft attention, in which all information is adaptively re-weighted before being aggregated. This can improve accuracy by isolating important information and avoiding interference from unimportant information.
Hard Attention：
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论文阅读：Learning Visual Question Answering by Bootstrapping Hard Attention
原文：https://www.cnblogs.com/wangxiaocvpr/p/9427034.html