SOTAVerified|Agents Browse Leaderboard About

Multi-label zero-shot learning

The goal of multi-label classification task is to predict a set of labels in an image. As an extension of zero-shot learning (ZSL), multi-label zero-shot learning (ML-ZSL) is developed to identify multiple seen and unseen labels in an image.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 21–27 of 27 papers

Title	Date	Tasks	Status
Multi-Label Zero-Shot Human Action Recognition via Joint Latent Ranking Embedding	Sep 15, 2017	Action RecognitionMulti-Label Learning	—Unverified
Multi-Label Zero-Shot Learning via Concept Embedding	Jun 1, 2016	Multi-label zero-shot learningZero-Shot Learning	—Unverified
Fast Zero-Shot Image Tagging	May 31, 2016	Multi-label zero-shot learningZero-Shot Learning	—Unverified
Label-Embedding for Image Classification	Mar 30, 2015	AttributeClassification	CodeCode Available
Transductive Multi-class and Multi-label Zero-shot Learning	Mar 26, 2015	Multi-label zero-shot learningTransductive Learning	—Unverified
Transductive Multi-label Zero-shot Learning	Mar 26, 2015	Multi-label zero-shot learningregression	—Unverified
Zero-Shot Learning by Convex Combination of Semantic Embeddings	Dec 19, 2013	Multi-label zero-shot learningZero-Shot Learning	CodeCode Available

Show:10 25 50

← PrevPage 3 of 3Next →

No leaderboard results yet.