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Akata, Z., Malinowski, M., Fritz, M., Schiele, B.: Multi-cue zero-shot learning with strong supervision. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
Akata, Z., Perronnin, F., Harchaoui, Z., Schmid, C.: Label embeddings for image classification. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 38(7), 1425–1438 (2016)
Biederman, I.: Recognition by components—a theory of human image understanding. Psychol. Rev. 94(2), 115–147 (1987)
Branson, S., Wah, C., Schroff, F., Babenko, B., Welinder, P., Perona, P., Belongie, S.: Visual recognition with humans in the loop. In: European Conference on Computer Vision (ECCV) (2010)
Christie, G., Parkash, A., Krothapalli, U., Parikh, D.: Predicting user annoyance using visual attributes. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., Vedaldi, A.: Describing textures in the wild. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2009)
Deza, A., Parikh, D.: Understanding image virality. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
Dhar, S., Ordonez, V., Berg, T.: High level describable attributes for predicting aesthetics and interestingness. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2011)
Donahue, J., Grauman, K.: Image recognition with annotator rationales. In: International Conference on Computer Vision (ICCV) (2011)
Douze, M., Ramisa, A., Schmid, C.: Combining attributes and fisher vectors for efficient image retrieval. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2011)
Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.A.: Describing objects by their attributes. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2009)
Feris, R.S., Bobbit, R., Brown, L., Pankanti, S.: Attribute-based people search: lessons learnt from a practical surveillance system. In: International Conference on Multimedia Retrieval (ICMR) (2014)
Gan, C., Yang, T., Gong, B.: Learning attributes equals multi-source domain generalization. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
He, K., Zhang, X., Ren, S., Sun, J.: Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In: International Conference on Computer Vision (ICCV) (2015)
Hendricks, L., Akata, Z., Rohrbach, M., Donahue, J., Schiele, B., Darrell, T.: Generating visual explanations. In: European Conference on Computer Vision (ECCV) (2016)
Huang, J., Feris, R.S., Chen, Q., Yan, S.: Cross-domain image retrieval with a dual attribute-aware ranking network. In: International Conference on Computer Vision (ICCV) (2015)
Isola, P., Xiao, J., Parikh, D., Torralba, A., Oliva, A.: What makes a photograph memorable? IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 36(7), 1469–1482 (2014)
Kong, S., Shen, X., Lin, Z., Mech, R., Fowlkes, C.: Photo aesthetics ranking network with attributes and content adaptation. In: European Conference on Computer Vision (ECCV) (2016)
Kovashka, A., Parikh, D., Grauman, K.: Whittlesearch: interactive image search with relative attribute feedback. Int. J. Comput. Vis. (IJCV) 115, 185–210 (2015)
Kovashka, A., Vijayanarasimhan, S., Grauman, K.: Actively selecting annotations among objects and attributes. In: International Conference on Computer Vision (ICCV) (2011)
Krizhevsky, A., Sutskever, I., Hinton, G.: Imagenet classification with deep convolutional neural networks. In: Conference on Neural Information Processing Systems (NIPS) (2012)
Kumar, N., Belhumeur, P.N., Nayar, S.K.: FaceTracer: A search engine for large collections of images with faces. In: European Conference on Computer Vision (ECCV) (2008)
Laffont, P.Y., Ren, Z., Tao, X., Qian, C., Hays, J.: Transient attributes for high-level understanding and editing of outdoor scenes. In: ACM SIGGRAPH (2014)
Lampert, C., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2009)
Lampert, C., Nickisch, H., Harmeling, S.: Attribute-based classification for zero-shot learning of object categories. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 36(3), 453–465 (2013)
Layne, R., T., H., Gong, S.: Re-id: Hunting attributes in the wild. In: British Machine Vision Conference (BMVC) (2014)
LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278–2324 (1998)
Liu, L., Xu, H., Xing, J., Liu, S., Zhou, X., Yan, S.: Wow! you are so beautiful today! In: International Conference on Multimedia (ACM MM) (2013)
Palatucci, M., Hinton, G., Pomerleau, D., Mitchell, T.M.: Zero-shot learning with semantic output codes. In: Conference on Neural Information Processing Systems (NIPS) (2009)
Parikh, D., Grauman, K.: Relative attributes. In: International Conference on Computer Vision (ICCV) (2011)
Patterson, G., Hays, J.: Sun attribute database: discovering, annotating, and recognizing scene attributes. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2012)
Qiao, R., Liu, L., Shen, C., van den Hengel, A.: Less is more: zero-shot learning from online textual documents with noise suppression. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)
Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I., Schiele, B.: What helps where and why? Semantic relatedness for knowledge transfer. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2010)
Schein, A., Popescul, A., Ungar, L., Pennock, D.: Methods and metrics for cold-start recommendations. In: International Conference on Research and Development in Information Retrieval (ACM SIGIR) (2002)
Sharmanska, V., Quadrianto, N., Lampert, C.: Learning to rank using privileged information. In: International Conference on Computer Vision (ICCV) (2013)
Shi, Z., Hospedales, T., Xiang, T.: Transferring a semantic representation for person re-identification and search. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
Siddiquie, B., Feris, R.S., Davis, L.: Image ranking and retrieval based on multi-attribute queries. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2011)
Su, C., Zhang, S., Xing, J., Gao, W., Tian, Q.: Deep attributes driven multi-camera person re-identification. In: European Conference on Computer Vision (ECCV) (2016)
Vaquero, D., Feris, R.S., Brown, L., Hampapur, A.: Attribute-based people search in surveillance environments. In: Winter Conference on Applications of Computer Vision (WACV) (2009)
Yan, X., Yang, J., Sohn, K., Le, H.: Attribute2image: Conditional image generation from visual attributes. In: European Conference on Computer Vision (ECCV) (2016)
Yang, S., Luo, P., Loy, C., Tang, X.: From facial part responses to face detection: a deep learning approach. In: International Conference on Computer Vision (ICCV) (2015)
Zhang, Z., Luo, P., Loy, C., Tang, X.: Learning deep representation for face alignment with auxiliary attributes. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 38(5), 918–930 (2015)
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Feris, R.S., Lampert, C., Parikh, D. (2017). Introduction to Visual Attributes. In: Feris, R., Lampert, C., Parikh, D. (eds) Visual Attributes. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-50077-5_1
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