(2019). A General Transductive Regularizer for Zero-Shot Learning. Presentation Conference Type, Conference Paper (Published). Conference Name, BMVC.
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Dec 8, 2020 · In this paper, we propose a General Transductive Regularizer (GTR), which assigns each unlabeled sample to a fixed attribute by defining a ...
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Aug 20, 2020 · ABSTRACT Most zero-shot learning (ZSL) methods based on generative adversarial networks (GANs) utilize random noise and semantic ...
This paper proposes a novel one-step approach that is able to perform zero-shot recognition in the original feature space by using directly trained ...
The training phase of GZSL methods can be divided into two broad settings: inductive learning and transductive learning [24]. Inductive learning utilises only ...
In this paper, we propose a straightforward yet effective method named. Quasi-Fully Supervised Learning (QFSL) to alleviate the bias problem. Our method follows ...
We propose an approach for scaling human-object interaction recognition in video data through the zero-shot learning technique to solve ...
This paper proposes a straightforward yet effective method named Quasi-Fully Supervised Learning (QFSL) to alleviate the bias problem in Zero-Shot Learning, ...
Abstract. In this paper, we propose a Visual Center Adaptation Method. (VCAM) to address the domain shift problem in zero-shot learning.