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Jul, 2016
双向潜在嵌入的零样本视觉识别
Zero-Shot Visual Recognition via Bidirectional Latent Embedding
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Qian Wang, Ke Chen
TL;DR
本文提出了一种分阶段的双向潜在嵌入识别框架,通过探索训练数据的拓扑和标签信息,在底部阶段创建了一个潜在嵌入空间,用于引导未知类别的半监督Sammon映射,通过最近邻法预测测试实例的标签,最终实验结果表明,该方法在零样本学习和归纳推理设置下达到了最先进的性能水平。
Abstract
zero-shot learning
for
visual recognition
, e.g., object and action recognition, has recently attracted a lot of attention. However, it still remains challenging in bridging the semantic gap between visual feature
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