{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:50Z","timestamp":1750220750973,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T00:00:00Z","timestamp":1587686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012659","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976158"],"award-info":[{"award-number":["61976158"]}],"id":[{"id":"10.13039\/501100012659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,4,24]]},"DOI":"10.1145\/3398329.3398353","type":"proceedings-article","created":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T04:43:15Z","timestamp":1590986595000},"page":"158-163","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Zero-Shot Image Classification via Consistent Subspace Learning"],"prefix":"10.1145","author":[{"given":"Shiwei","family":"Chen","sequence":"first","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electronic and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,5,31]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of Neural Information Processing Systems (NIPS'12)","author":"Krizhevsky A.","year":"2012","unstructured":"A. Krizhevsky , I. Sutskever , and G. E. Hinton . Imagenet classification with deep convolutional neural networks . In Proceedings of Neural Information Processing Systems (NIPS'12) , ACM, Lake Tahoe, Nevada, USA, Dec., pages 1097--1105 , 2012 . A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Proceedings of Neural Information Processing Systems (NIPS'12), ACM, Lake Tahoe, Nevada, USA, Dec., pages 1097--1105, 2012."},{"key":"e_1_3_2_1_2_1","first-page":"1","volume-title":"Proceedings of Computer Vision and Pattern Recognition (CVPR'15)","author":"Szegedy C.","year":"2015","unstructured":"C. Szegedy , W. Liu , Y. Jia , P. Sermanet , S. Reed , D. Anguelov , D. Erhan , V. Vanhoucke , and A. Rabinovich . Going deeper with convolutions , In Proceedings of Computer Vision and Pattern Recognition (CVPR'15) , IEEE , Boston, Massachusetts , Jun., pages 1 -- 9 , 2015 . C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. Going deeper with convolutions, In Proceedings of Computer Vision and Pattern Recognition (CVPR'15), IEEE, Boston, Massachusetts, Jun., pages 1--9, 2015."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2723400"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.140"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00227"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2947780"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00717"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2400461"},{"key":"e_1_3_2_1_11_1","first-page":"2142","volume-title":"Proceedings of Computer Vision and Pattern Recognition (CVPR'15)","author":"Yao T.","year":"2015","unstructured":"T. Yao , Y. Pan , C. W. Ngo , H. Li., T. Mei . Semi-supervised domain adaptation with subspace learning for visual recognition . In Proceedings of Computer Vision and Pattern Recognition (CVPR'15) , IEEE , Boston, Massachusetts , Jun., pages 2142 -- 2150 , 2015 . T. Yao, Y. Pan, C. W. Ngo, H. Li., T. Mei. Semi-supervised domain adaptation with subspace learning for visual recognition. In Proceedings of Computer Vision and Pattern Recognition (CVPR'15), IEEE, Boston, Massachusetts, Jun., pages 2142--2150, 2015."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.03.026"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of Neural Information Processing Systems (NIPS'14)","author":"Jayaraman D.","year":"2014","unstructured":"D. Jayaraman , and K. Grauman . Zero-shot recognition with unreliable attributes . In Proceedings of Neural Information Processing Systems (NIPS'14) , ACM, Montr\u00e9al, Canada, Dec., pages 3464--3472 , 2014 . D. Jayaraman, and K. Grauman. Zero-shot recognition with unreliable attributes. In Proceedings of Neural Information Processing Systems (NIPS'14), ACM, Montr\u00e9al, Canada, Dec., pages 3464--3472, 2014."},{"key":"e_1_3_2_1_14_1","first-page":"1410","volume-title":"Proceedings of Neural Information Processing Systems (NIPS'09)","author":"Palatucci M.","year":"2009","unstructured":"M. Palatucci , D. Pomerleau , G. E. Hinton , and T. M. Mitchell . Zero-shot learning with semantic output codes . In Proceedings of Neural Information Processing Systems (NIPS'09) , ACM , Vancouver, Canada , Dec., pages 1410 -- 1418 , 2009 . M. Palatucci, D. Pomerleau, G. E. Hinton, and T. M. Mitchell. Zero-shot learning with semantic output codes. In Proceedings of Neural Information Processing Systems (NIPS'09), ACM, Vancouver, Canada, Dec., pages 1410--1418, 2009."},{"key":"e_1_3_2_1_15_1","first-page":"3174","volume-title":"Computer Vision and Pattern Recognition (CVPR'17)","author":"Kodirov E.","year":"2017","unstructured":"E. Kodirov , T. Xiang , and S. Gong . Semantic autoencoder for zero-shot learning . In Computer Vision and Pattern Recognition (CVPR'17) , IEEE , Honolulu, Hawaii, USA , Jul., pages 3174 -- 3183 , 2017 . E. Kodirov, T. Xiang, and S. Gong. Semantic autoencoder for zero-shot learning. In Computer Vision and Pattern Recognition (CVPR'17), IEEE, Honolulu, Hawaii, USA, Jul., pages 3174--3183, 2017."},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of Neural Information Processing Systems (NIPS'13)","author":"Socher R.","year":"2013","unstructured":"R. Socher , M. Ganjoo , C. D. Manning , and A. Ng . Zero-shot learning through cross-modal transfer . In Proceedings of Neural Information Processing Systems (NIPS'13) , ACM, Lake Tahoe, Nevada, USA, Dec., pages 935--943 , 2013 . R. Socher, M. Ganjoo, C. D. Manning, and A. Ng. Zero-shot learning through cross-modal transfer. In Proceedings of Neural Information Processing Systems (NIPS'13), ACM, Lake Tahoe, Nevada, USA, Dec., pages 935--943, 2013."},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of International Conference on Computer Vision (CVPR'15)","author":"Swersky K.","year":"2015","unstructured":"Lei Ba, Jimmy, K. Swersky , and S. Fidler . Predicting deep zero-shot convolutional neural networks using textual descriptions . In Proceedings of International Conference on Computer Vision (CVPR'15) , IEEE, Boston, Massachusetts, Jun., pages 4247--4255 , 2015 . Lei Ba, Jimmy, K. Swersky, and S. Fidler. Predicting deep zero-shot convolutional neural networks using textual descriptions. In Proceedings of International Conference on Computer Vision (CVPR'15), IEEE, Boston, Massachusetts, Jun., pages 4247--4255, 2015."},{"key":"e_1_3_2_1_18_1","volume-title":"Zero-shot learning by convex combination of semantic embeddings. In arXiv preprint arXiv:1312.5650","author":"Norouzi M.","year":"2013","unstructured":"M. Norouzi , T. Mikolov , S. Bengio , Y. Singer , J. Shlens , A. Frome , and J. Dean . Zero-shot learning by convex combination of semantic embeddings. In arXiv preprint arXiv:1312.5650 , 2013 . M. Norouzi, T. Mikolov, S. Bengio, Y. Singer, J. Shlens, A. Frome, and J. Dean. Zero-shot learning by convex combination of semantic embeddings. In arXiv preprint arXiv:1312.5650, 2013."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.15"},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of International Conference on Computer Vision (ICCV'15)","author":"Kodirov E.","year":"2015","unstructured":"E. Kodirov , T. Xiang , Z. Fu , and S. Gong . Unsupervised domain adap- tation for zero-shot learning . In Proceedings of International Conference on Computer Vision (ICCV'15) , IEEE, Santiago, Chile, Apr., pages 2452--2460 , 2015 . E. Kodirov, T. Xiang, Z. Fu, and S. Gong. Unsupervised domain adap- tation for zero-shot learning. In Proceedings of International Conference on Computer Vision (ICCV'15), IEEE, Santiago, Chile, Apr., pages 2452--2460, 2015."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.376"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of Computer Vision and Pattern Recognition (CVPR'17)","author":"Zhang L.","year":"2021","unstructured":"L. Zhang , T. Xiang , and S. Gong . Learning a deep embedding model for zero-shot learning . In Proceedings of Computer Vision and Pattern Recognition (CVPR'17) , IEEE, Honolulu, Hawaii, USA, Jul., pages 2021 - 2030, 2017. L. Zhang, T. Xiang, and S. Gong. Learning a deep embedding model for zero-shot learning. In Proceedings of Computer Vision and Pattern Recognition (CVPR'17), IEEE, Honolulu, Hawaii, USA, Jul., pages 2021- 2030, 2017."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.474"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.649"},{"key":"e_1_3_2_1_25_1","volume-title":"Proceedings of International Conference on Multimedia and Expo (ICME'19)","author":"Liu G.","year":"2019","unstructured":"G. Liu , J. Guan , M. Zhang , J. Zhang , Z. Wang , and Z. Lu . Joint pro- jection and subspace learning for zero-shot recognition . In Proceedings of International Conference on Multimedia and Expo (ICME'19) , IEEE, Shanghai, China, Jul., pages 1228--1233 , 2019 . G. Liu, J. Guan, M. Zhang, J. Zhang, Z. Wang, and Z. Lu. Joint pro- jection and subspace learning for zero-shot recognition. In Proceedings of International Conference on Multimedia and Expo (ICME'19), IEEE, Shanghai, China, Jul., pages 1228--1233, 2019."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.575"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of Computer Vision and Pattern Recognition (CVPR'12)","author":"Patterson G.","year":"2012","unstructured":"G. Patterson , and J. Hays . Sun attribute database: Discovering, anno- tating, and recognizing scene attributes . In Proceedings of Computer Vision and Pattern Recognition (CVPR'12) , IEEE, rhode island, USA, Jun., pages 2751--2758 , 2012 . G. Patterson, and J. Hays. Sun attribute database: Discovering, anno- tating, and recognizing scene attributes. In Proceedings of Computer Vision and Pattern Recognition (CVPR'12), IEEE, rhode island, USA, Jun., pages 2751--2758, 2012."},{"key":"e_1_3_2_1_28_1","first-page":"2251","article-title":"Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly","volume":"4","author":"Xian Y.","year":"2018","unstructured":"Y. Xian , C. H. Lampert , B. Schiele , and Z. Akata . Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly . IEEE Transactions on Pattern Analysis and Machine Intelligence , 4 1 (9): 2251 -- 2265 , 2018 . Y. Xian, C. H. Lampert, B. Schiele, and Z. Akata. Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence, 4 1 (9): 2251--2265, 2018.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206772"},{"key":"e_1_3_2_1_30_1","volume-title":"The caltech-ucsd birds-200-2011 dataset","author":"Wah C.","year":"2011","unstructured":"C. Wah , S. Branson , P Welinder , P. Perona , and S. Belongie . The caltech-ucsd birds-200-2011 dataset , 2011 . C. Wah, S. Branson, P Welinder, P. Perona, and S. Belongie. The caltech-ucsd birds-200-2011 dataset, 2011."}],"event":{"name":"CNIOT2020: 2020 International Conference on Computing, Networks and Internet of Things","sponsor":["University of Salamanca University of Salamanca","The University of Adelaide, Australia","Edinburgh Napier University, UK Edinburgh Napier University, UK","University of Sydney Australia"],"location":"Sanya China","acronym":"CNIOT2020"},"container-title":["Proceedings of the 2020 International Conference on Computing, Networks and Internet of Things"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3398329.3398353","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3398329.3398353","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:53Z","timestamp":1750199933000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3398329.3398353"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,24]]},"references-count":30,"alternative-id":["10.1145\/3398329.3398353","10.1145\/3398329"],"URL":"https:\/\/doi.org\/10.1145\/3398329.3398353","relation":{},"subject":[],"published":{"date-parts":[[2020,4,24]]},"assertion":[{"value":"2020-05-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}