Zero-shot object recognition by semantic manifold distance

Keywords

Embedding, Semantic similarity, Computer science, Manifold (fluid mechanics), Artificial intelligence

References

• Efficient Estimation of Word Representations in Vector SpaceTomáš Mikolov, Kai Chen, Greg S. Corrado — 2013
• Single-example Learning of Novel Classes using Representation by SimilarityEvgeniy Bart, Shimon Ullman — 2005
• What helps where – and why? Semantic relatedness for knowledge transferMarcus Rohrbach, Michael Stark, György Szarvas — 2010
• Attribute-centric recognition for cross-category generalizationAli Farhadi, Ian Endres, Derek Hoiem — 2010
• COSTA: Co-Occurrence Statistics for Zero-Shot ClassificationThomas Mensink, Efstratios Gavves, Cees G. M. Snoek — 2014
• Evaluating knowledge transfer and zero-shot learning in a large-scale settingMarcus Rohrbach, Michael Stark, Bernt Schiele — 2011
• Describing objects by their attributesAli Farhadi, Ian Endres, Derek Hoiem — 2009
• ImageNet: A large-scale hierarchical image databaseJia Deng, Wei Dong, Richard Socher — 2009
• Label-Embedding for Attribute-Based ClassificationZeynep Akata, Florent Perronnin, Zaïd Harchaoui — 2013
• Cluster Kernels for Semi-Supervised LearningOlivier Chapelle, Jason Weston, Bernhard Schölkopf — 2002
• LIBLINEAR: A Library for Large Linear ClassificationRong-En Fan, Kai‐Wei Chang, Cho‐Jui Hsieh — 2008
• DeViSE: A Deep Visual-Semantic Embedding ModelAndrea Frome, Greg S. Corrado, Jon Shlens — 2013
• Zero-Shot Learning Through Cross-Modal TransferRichard Socher, Milind Ganjoo, Sridhar, Hamsa — 2013
• Learning Visual AttributesVittorio Ferrari, Andrew Zisserman — 2007
• Combining active learning and semi-supervised learning using Gaussian fields and harmonic functionsXiaojin Zhu, John Lafferty, Zoubin Ghahramani — 2003
• Learning to detect unseen object classes by between-class attribute transferChristoph H. Lampert, Hannes Nickisch, Stefan Harmeling — 2009
• Zero-shot Learning with Semantic Output CodesMark Palatucci, Dean Pomerleau, Geoffrey E. Hinton — 2009
• Transfer Learning in a Transductive SettingMarcus Rohrbach, Sandra Ebert, Bernt Schiele — 2013
• Distributed Representations of Words and Phrases and their CompositionalityTomáš Mikolov, Ilya Sutskever, Kai Chen — 2013
• Designing Category-Level Attributes for Discriminative Visual RecognitionFelix X. Yu, Liangliang Cao, Rogério Feris — 2013

Cited by

• Recognizing unknown objects with attributes relationship modelWai Lam Hoo, Chee Seng Chan — 2015
• Unsupervised Domain Adaptation for Zero-Shot LearningElyor Kodirov, Tao Xiang, Zhenyong Fu — 2015
• Classifying Unseen Instances by Learning Class-Independent Similarity FunctionsZiming Zhang, Venkatesh Saligrama — 2015
• Synthesized Classifiers for Zero-Shot LearningSoravit Changpinyo, Wei‐Lun Chao, Boqing Gong — 2016
• Less is More: Zero-Shot Learning from Online Textual Documents with Noise SuppressionRuizhi Qiao, Lingqiao Liu, Chunhua Shen — 2016
• Learning Attributes Equals Multi-Source Domain GeneralizationChuang Gan, Tianbao Yang, Boqing Gong — 2016
• cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurveyHirokatsu Kataoka, Yudai Miyashita, Tomoaki K. Yamabe — 2016
• Zero-Shot Learning via Joint Latent Similarity EmbeddingZiming Zhang, Venkatesh Saligrama — 2015
• Zero-shot learning with Multi-Battery Factor AnalysisZhong Ji, Yuzhong Xie, Yanwei Pang — 2016
• Exploring synonyms as context in zero-shot action recognitionIoannis Alexiou, Tao Xiang, Shaogang Gong — 2016
• Transductive Zero-Shot Recognition via Shared Model Space LearningYuchen Guo, Guiguang Ding, Xiaoming Jin — 2016
• Beyond Semantic Attributes: Discrete Latent Attributes Learning for Zero-Shot RecognitionJie Qin, Yunhong Wang, Li Liu — 2016
• Adaptation of Word Vectors using Tree Structure for Visual SemanticsNakamasa Inoue, Koichi Shinoda — 2016
• Manifold regularized cross-modal embedding for zero-shot learningZhong Ji, Yunlong Yu, Yanwei Pang — 2017
• Local Similarity-Aware Deep Feature EmbeddingChen Huang, Chen Change Loy, Xiaoou Tang — 2016
• Learning a Deep Embedding Model for Zero-Shot LearningLi Zhang, Tao Xiang, Shaogang Gong — 2016
• Learning Joint Feature Adaptation for Zero-Shot RecognitionZiming Zhang, Venkatesh Saligrama — 2016
• Zero-Shot Learning via Revealing Data DistributionBo Zhao, Tao Wu, Tianfu Wu — 2016
• Transductive Zero-Shot Action Recognition by Word-Vector EmbeddingXun Xu, Timothy M. Hospedales, Shaogang Gong — 2015
• Gaussian Visual-Linguistic Embedding for Zero-Shot RecognitionTanmoy Mukherjee, Timothy Hospedales — 2016

Related papers

• Overview of nonlinear dimensionality reduction methods in manifold learningZhao Liu — 2007
• Nonlinear Dimensionality Reduction Method Based on Manifold LearningRui Xiao, Liyuan Zhang — 2012
• Learning a Joint Manifold Representation from Multiple Data SetsMarwan Torki, Ahmed Elgammal, Chan Su Lee — 2010
• Deep Manifold Computing and VisualizationStan Z. Li, Zelin Zang, Lirong Wu — 2020
• Analysis of Commute Time Embedding Based on Spectral GraphHee-Il Hahn — 2014
• Manifold-aligned Neighbor EmbeddingMohammad Tariqul Islam, Jason W. Fleischer — 2022
• Manifold Learning and its Application on Head Pose EstimationJue Wang — 2010