Zero-shot learning via category-specific visual-semantic mapping and label refinement

• المؤلفون الرئيسيون: Niu, Li, Cai, Jianfei, Veeraraghavan, Ashok, Zhang, Liqing
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Zero-shot Learning (ZSL); Domain Adaptation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/142785

Zero-shot learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories in which the gap between seen categories and unseen categories is generally bridged via visual-semantic mapping between the low-level visual feature space and the in...