메뉴 건너뛰기




Volumn , Issue , 2013, Pages 819-826

Label-embedding for attribute-based classification

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATIVE SOURCE; ATTRIBUTE VECTORS; ATTRIBUTE-BASED; CLASS HIERARCHIES; INTERMEDIATE REPRESENTATIONS; LEARNING SCENARIOS; PARAMETER SHARING; TRAINING DATA;

EID: 84887338331     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.111     Document Type: Conference Paper
Times cited : (752)

References (43)
  • 1
    • 77953177813 scopus 로고    scopus 로고
    • Uncovering shared structures in multiclass classification
    • 2, 3
    • Y. Amit, M. Fink, N. Srebro, and S. Ullman. Uncovering shared structures in multiclass classification. In ICML, 2007. 2, 3
    • (2007) ICML
    • Amit, Y.1    Fink, M.2    Srebro, N.3    Ullman, S.4
  • 2
    • 85162050606 scopus 로고    scopus 로고
    • Label embedding trees for large multi-class tasks
    • 2, 3
    • S. Bengio, J. Weston, and D. Grangier. Label embedding trees for large multi-class tasks. In NIPS, 2010. 2, 3
    • (2010) NIPS
    • Bengio, S.1    Weston, J.2    Grangier, D.3
  • 4
    • 84898420173 scopus 로고    scopus 로고
    • The devil is in the details: An evaluation of recent feature encoding methods
    • 2, 5
    • K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman. The devil is in the details: an evaluation of recent feature encoding methods. In BMVC, 2011. 2, 5
    • (2011) BMVC
    • Chatfield, K.1    Lempitsky, V.2    Vedaldi, A.3    Zisserman, A.4
  • 6
    • 80052872247 scopus 로고    scopus 로고
    • Visual and semantic similarity in ImageNet
    • 2
    • T. Deselaers and V. Ferrari. Visual and semantic similarity in ImageNet. In CVPR, 2011. 2
    • (2011) CVPR
    • Deselaers, T.1    Ferrari, V.2
  • 7
    • 80052883815 scopus 로고    scopus 로고
    • Combining attributes and Fisher vectors for efficient image retrieval
    • 2
    • M. Douze, A. Ramisa, and C. Schmid. Combining attributes and Fisher vectors for efficient image retrieval. In CVPR, 2011. 2
    • (2011) CVPR
    • Douze, M.1    Ramisa, A.2    Schmid, C.3
  • 9
    • 70450219358 scopus 로고    scopus 로고
    • Learning visual attributes
    • 2
    • V. Ferrari and A. Zisserman. Learning visual attributes. In NIPS, 2007. 2
    • (2007) NIPS
    • Ferrari, V.1    Zisserman, A.2
  • 10
    • 84863232701 scopus 로고    scopus 로고
    • Ranking model adaptation for domain-specific search
    • 4
    • B. Geng, L. Yang, C. Xu, and X.-S. Hua. Ranking model adaptation for domain-specific search. IEEE TKDE, 2012. 4
    • (2012) IEEE TKDE
    • Geng, B.1    Yang, L.2    Xu, C.3    Hua, X.-S.4
  • 12
    • 77956528679 scopus 로고    scopus 로고
    • Multi-label prediction via compressed sensing
    • 2
    • D. Hsu, S. Kakade, J. Langford, and T. Zhang. Multi-label prediction via compressed sensing. In NIPS, 2009. 2
    • (2009) NIPS
    • Hsu, D.1    Kakade, S.2    Langford, J.3    Zhang, T.4
  • 13
    • 84875881757 scopus 로고    scopus 로고
    • Product quantization for nearest neighbor search
    • 2, 5
    • H. Jégou, M. Douze, and C. Schmid. Product quantization for nearest neighbor search. IEEE TPAMI, 2011. 2, 5
    • (2011) IEEE TPAMI
    • Jégou, H.1    Douze, M.2    Schmid, C.3
  • 15
    • 77951193770 scopus 로고    scopus 로고
    • FaceTracer: A search engine for large collections of images with faces
    • 2
    • N. Kumar, P. Belhummeur, and S. Nayar. FaceTracer: A search engine for large collections of images with faces. In ECCV, 2008. 2
    • (2008) ECCV
    • Kumar, N.1    Belhummeur, P.2    Nayar, S.3
  • 16
    • 70450172710 scopus 로고    scopus 로고
    • Learning to detect unseen object classes by between-class attribute transfer
    • 1, 2, 3, 4, 5, 6
    • C. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009. 1, 2, 3, 4, 5, 6
    • (2009) CVPR
    • Lampert, C.1    Nickisch, H.2    Harmeling, S.3
  • 17
    • 74549123074 scopus 로고    scopus 로고
    • Zero-data learning of new tasks
    • 1, 2, 3
    • H. Larochelle, D. Erhan, and Y. Bengio. Zero-data learning of new tasks. In AAAI, 2008. 1, 2, 3
    • (2008) AAAI
    • Larochelle, H.1    Erhan, D.2    Bengio, Y.3
  • 18
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • 5
    • D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60:91-110, 2004. 5
    • (2004) IJCV , vol.60 , pp. 91-110
    • Lowe, D.G.1
  • 19
    • 84856659292 scopus 로고    scopus 로고
    • A joint learning framework for attribute models and object descriptions
    • 2
    • D. Mahajan, S. Sellamanickam, and V. Nair. A joint learning framework for attribute models and object descriptions. In ICCV, 2011. 2
    • (2011) ICCV
    • Mahajan, D.1    Sellamanickam, S.2    Nair, V.3
  • 20
    • 77953184603 scopus 로고    scopus 로고
    • Max-margin additive classifiers for detection
    • 2
    • S. Maji and A. Berg. Max-margin additive classifiers for detection. In ICCV, 2009. 2
    • (2009) ICCV
    • Maji, S.1    Berg, A.2
  • 21
    • 84898449992 scopus 로고    scopus 로고
    • Tree-structured CRF models for interactive image labeling
    • 2
    • T. Mensink, J. Verbeek, and G. Csurka. Tree-structured CRF models for interactive image labeling. IEEE TPAMI, 2012. 2
    • (2012) IEEE TPAMI
    • Mensink, T.1    Verbeek, J.2    Csurka, G.3
  • 22
    • 84883488616 scopus 로고    scopus 로고
    • Metric learning for large scale image classification: Generalizing to new classes at near-zero cost
    • 2
    • T. Mensink, J. Verbeek, F. Perronnin, and G. Csurka. Metric learning for large scale image classification: Generalizing to new classes at near-zero cost. In ECCV, 2012. 2
    • (2012) ECCV
    • Mensink, T.1    Verbeek, J.2    Perronnin, F.3    Csurka, G.4
  • 23
    • 85162522202 scopus 로고    scopus 로고
    • Im2Text: Describing images using 1 million captioned photographs
    • 2
    • V. Ordonez, G. Kulkarni, and T. Berg. Im2Text: Describing images using 1 million captioned photographs. In NIPS, 2011. 2
    • (2011) NIPS
    • Ordonez, V.1    Kulkarni, G.2    Berg, T.3
  • 25
  • 26
    • 79959771606 scopus 로고    scopus 로고
    • Improving the Fisher kernel for large-scale image classification
    • 2, 5
    • F. Perronnin, J. Sánchez, and T. Mensink. Improving the Fisher kernel for large-scale image classification. In ECCV, 2010. 2, 5
    • (2010) ECCV
    • Perronnin, F.1    Sánchez, J.2    Mensink, T.3
  • 27
    • 80052892795 scopus 로고    scopus 로고
    • Evaluating knowledge transfer and zero-shot learning in a large-scale setting
    • 2
    • M. Rohrbach, M. Stark, and B. Schiele. Evaluating knowledge transfer and zero-shot learning in a large-scale setting. In CVPR, 2011. 2
    • (2011) CVPR
    • Rohrbach, M.1    Stark, M.2    Schiele, B.3
  • 28
    • 77955989949 scopus 로고    scopus 로고
    • What hepls here-and why? Semantic relatedness for knowledge transfer
    • 2
    • M. Rohrbach, M. Stark, G. Szarvas, I. Gurevych, and B. Schiele. What hepls here-and why? Semantic relatedness for knowledge transfer. In CVPR, 2010. 2
    • (2010) CVPR
    • Rohrbach, M.1    Stark, M.2    Szarvas, G.3    Gurevych, I.4    Schiele, B.5
  • 29
    • 33847702103 scopus 로고    scopus 로고
    • The principal components analysis of a graph, and its relationships to spectral clustering
    • 4
    • M. Saerens, F. Fouss, L. Yen, and P. Dupont. The principal components analysis of a graph, and its relationships to spectral clustering. In ECML, 2004. 4
    • (2004) ECML
    • Saerens, M.1    Fouss, F.2    Yen, L.3    Dupont, P.4
  • 30
    • 80052885179 scopus 로고    scopus 로고
    • High-dimensional signature compression for large-scale image classification
    • 2
    • J. Sánchez and F. Perronnin. High-dimensional signature compression for large-scale image classification. In CVPR, 2011. 2
    • (2011) CVPR
    • Sánchez, J.1    Perronnin, F.2
  • 33
    • 80052894348 scopus 로고    scopus 로고
    • Image ranking and retrieval based on multi-attribute queries
    • 2
    • B. Siddiquie, R. Feris, and L. Davis. Image ranking and retrieval based on multi-attribute queries. In CVPR, 2011. 2
    • (2011) CVPR
    • Siddiquie, B.1    Feris, R.2    Davis, L.3
  • 34
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • 3, 4
    • I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. Large margin methods for structured and interdependent output variables. JMLR, 2005. 3, 4
    • (2005) JMLR
    • Tsochantaridis, I.1    Joachims, T.2    Hofmann, T.3    Altun, Y.4
  • 35
    • 77955989063 scopus 로고    scopus 로고
    • Efficient additive kernels via explicit feature maps
    • 2
    • A. Vedaldi and A. Zisserman. Efficient additive kernels via explicit feature maps. In CVPR, 2010. 2
    • (2010) CVPR
    • Vedaldi, A.1    Zisserman, A.2
  • 36
    • 84866644207 scopus 로고    scopus 로고
    • Sparse kernel approximations for efficient classification and detection
    • 2
    • A. Vedaldi and A. Zisserman. Sparse kernel approximations for efficient classification and detection. In CVPR, 2012. 2
    • (2012) CVPR
    • Vedaldi, A.1    Zisserman, A.2
  • 37
    • 84856635994 scopus 로고    scopus 로고
    • Multiclass recognition and part localization with humans in the loop
    • 2, 4, 6
    • C. Wah, S. Branson, P. Perona, and S. Belongie. Multiclass recognition and part localization with humans in the loop. In ICCV, 2011. 2, 4, 6
    • (2011) ICCV
    • Wah, C.1    Branson, S.2    Perona, P.3    Belongie, S.4
  • 38
    • 77953177673 scopus 로고    scopus 로고
    • Joint learning of visual attributes, object classes and visual saliency
    • 2
    • G. Wang and D. Forsyth. Joint learning of visual attributes, object classes and visual saliency. In ICCV, 2009. 2
    • (2009) ICCV
    • Wang, G.1    Forsyth, D.2
  • 39
    • 80052913382 scopus 로고    scopus 로고
    • A discriminative latent model of object classes and attributes
    • 2
    • Y. Wang and G. Mori. A discriminative latent model of object classes and attributes. In ECCV, 2010. 2
    • (2010) ECCV
    • Wang, Y.1    Mori, G.2
  • 40
    • 84881041525 scopus 로고    scopus 로고
    • Large margin taxonomy embedding for document categorization
    • 2, 3
    • K. Weinberger and O. Chapelle. Large margin taxonomy embedding for document categorization. In NIPS, 2008. 2, 3
    • (2008) NIPS
    • Weinberger, K.1    Chapelle, O.2
  • 41
    • 77955654853 scopus 로고    scopus 로고
    • Large scale image annotation: Learning to rank with joint word-image embeddings
    • 2, 3, 4, 7
    • J. Weston, S. Bengio, and N. Usunier. Large scale image annotation: Learning to rank with joint word-image embeddings. ECML, 2010. 2, 3, 4, 7
    • (2010) ECML
    • Weston, J.1    Bengio, S.2    Usunier, N.3
  • 43
    • 84855413670 scopus 로고    scopus 로고
    • Attribute-based transfer learning for object categorization with zero or one training example
    • 2
    • X. Yu and Y. Aloimonos. Attribute-based transfer learning for object categorization with zero or one training example. In ECCV, 2010. 2
    • (2010) ECCV
    • Yu, X.1    Aloimonos, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.