Multi-label zero-shot learning (ML-ZSL) strives to recognize all objects in an image, regardless of whether they are present in the training data. Recent methods incorporate an attention mechanism to locate labels in the image and generate class-specific semantic information. However, the ...
《Multi-Label Zero-Shot Learning With Structured Knowledge Graphs》论文笔记,程序员大本营,技术文章内容聚合第一站。
In this paper, for the first time, we investigate and formalise a general framework for multi-label zero-shot learning, addressing the unique challenge therein: how to exploit multi-label correlation at test time with no training data for those classes? In particular, we propose (1) a multi...
相比之下,多标签零镜头学习(multi-label zero-shot learning, ZSL)的任务是在测试时间识别图像中的多个新的未见类别,而在训练过程中没有看到相应的视觉示例。在通用ZSL (GZSL)设置中,测试图像可以同时包含多个可见和不可见类。在大规模的多标签设置中,GZSL是特别具有挑战性的,在这种情况下,一个图像中会出现多个不...
This repository contains the implementation ofShared Attention for Multi-label Zero-shot Learning. In this work, we address zero-shot multi-label learning for recognition all (un)seen labels using a shared multi-attention method with a novel training mechanism. ...
Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces Large multi-label datasets contain labels that occur thousands of times (frequent group), those that occur only a few times (few-shot group), and labels that never appear in the training dataset (zero-shot group). Multi...
2021-01-15论文笔记:Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces,程序员大本营,技术文章内容聚合第一站。
Generalized Zero-Shot Extreme Multi-label Learning Nilesh Gupta, Sakina Bohra, Yashoteja Prabhu, Saurabh Purohit, Manik Varma 2021 Knowledge Discovery and Data Mining|August 2021 Published by ACM Publication Download BibTex Extreme Multi-label Learning (XML) involves assigning the subset of most relev...
bionlproc/multi-label-zero-shotofficial 20 Tasks Edit AddRemove General ClassificationMulti-Label ClassificationMulti-Label LearningMulti Label Text ClassificationMulti-Label Text Classificationtext-classificationText Classification Datasets Add Datasetsintroduced or used in this paper ...
Few/Zero-shot learning is a big challenge of many classifications tasks, where a classifier is required to recognise instances of classes that have very few or even no training samples. It becomes more difficult in multi-label classification, where each instance is labelled with more than one ...