{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:26:50Z","timestamp":1772908010618,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3416269","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T12:26:25Z","timestamp":1602505585000},"page":"3007-3015","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Few-Shot Ensemble Learning for Video Classification with SlowFast Memory Networks"],"prefix":"10.1145","author":[{"given":"Mengshi","family":"Qi","sequence":"first","affiliation":[{"name":"Ecole polytechnique federale de Lausanne (EPFL), Lausanne, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Qin","sequence":"additional","affiliation":[{"name":"Inception Institute of Arti!cial Intelligence (IIAI), Abu Dhabi, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiantong","family":"Zhen","sequence":"additional","affiliation":[{"name":"Universiteit van Amsterdam, Abu Dhabi, Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Di","family":"Huang","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, Sydney, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiebo","family":"Luo","sequence":"additional","affiliation":[{"name":"University of Rochester, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Bagging predictors. Machine learning","author":"Breiman Leo","year":"1996","unstructured":"Leo Breiman . 1996. Bagging predictors. Machine learning , Vol. 24 , 2 ( 1996 ), 123--140. Leo Breiman. 1996. Bagging predictors. Machine learning, Vol. 24, 2 (1996), 123--140."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123437"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.502"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123349"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350895"},{"key":"e_1_3_2_2_6_1","volume-title":"Proc","author":"Dalal Navneet","unstructured":"Navneet Dalal , Bill Triggs , and Cordelia Schmid . 2006. Human detection using oriented histograms of flow and appearance . In Proc . ECCV. Springer , 428--441. Navneet Dalal, Bill Triggs, and Cordelia Schmid. 2006. Human detection using oriented histograms of flow and appearance. In Proc. ECCV. Springer, 428--441."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240571"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00630"},{"key":"e_1_3_2_2_9_1","volume-title":"Proc. NIPS. 3468--3476","author":"Feichtenhofer Christoph","year":"2016","unstructured":"Christoph Feichtenhofer , Axel Pinz , and Richard Wildes . 2016 . Spatiotemporal residual networks for video action recognition . In Proc. NIPS. 3468--3476 . Christoph Feichtenhofer, Axel Pinz, and Richard Wildes. 2016. Spatiotemporal residual networks for video action recognition. In Proc. NIPS. 3468--3476."},{"key":"e_1_3_2_2_10_1","volume-title":"Proc. ICML.","author":"Finn Chelsea","year":"2017","unstructured":"Chelsea Finn , Pieter Abbeel , and Sergey Levine . 2017 . Model-agnostic meta-learning for fast adaptation of deep networks . In Proc. ICML. Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In Proc. ICML."},{"key":"e_1_3_2_2_11_1","volume-title":"The elements of statistical learning","author":"Friedman Jerome","unstructured":"Jerome Friedman , Trevor Hastie , and Robert Tibshirani . 2001. The elements of statistical learning . Vol. 1 . Springer series in statistics New York. Jerome Friedman, Trevor Hastie, and Robert Tibshirani. 2001. The elements of statistical learning. Vol. 1. Springer series in statistics New York."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Jerome Friedman Trevor Hastie Robert Tibshirani etal 2000. Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). The annals of statistics Vol. 28 2 (2000) 337--407.  Jerome Friedman Trevor Hastie Robert Tibshirani et al. 2000. Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). The annals of statistics Vol. 28 2 (2000) 337--407.","DOI":"10.1214\/aos\/1016218223"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240566"},{"key":"e_1_3_2_2_14_1","volume-title":"Proc. ICLR","author":"Garcia Victor","year":"2018","unstructured":"Victor Garcia and Joan Bruna . 2018 . Few-shot learning with graph neural networks . Proc. ICLR (2018). Victor Garcia and Joan Bruna. 2018. Few-shot learning with graph neural networks. Proc. ICLR (2018)."},{"key":"e_1_3_2_2_15_1","volume-title":"Proc","author":"He Kaiming","unstructured":"Kaiming He , Xiangyu Zhang , Shaoqing Ren , and Jian Sun . 2016. Identity mappings in deep residual networks . In Proc . ECCV. Springer , 630--645. Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Identity mappings in deep residual networks. In Proc. ECCV. Springer, 630--645."},{"key":"e_1_3_2_2_16_1","volume-title":"Long short-term memory. Neural computation","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber . 1997. Long short-term memory. Neural computation , Vol. 9 , 8 ( 1997 ), 1735--1780. Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation, Vol. 9, 8 (1997), 1735--1780."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351088"},{"key":"e_1_3_2_2_18_1","volume-title":"Proc. ICLR.","author":"Kaiser \u0141ukasz","year":"2017","unstructured":"\u0141ukasz Kaiser , Ofir Nachum , Aurko Roy , and Samy Bengio . 2017 . Learning to remember rare events . In Proc. ICLR. \u0141ukasz Kaiser, Ofir Nachum, Aurko Roy, and Samy Bengio. 2017. Learning to remember rare events. In Proc. ICLR."},{"key":"e_1_3_2_2_19_1","unstructured":"Will Kay Joao Carreira Karen Simonyan Brian Zhang Chloe Hillier Sudheendra Vijayanarasimhan Fabio Viola Tim Green Trevor Back Paul Natsev etal 2017. The kinetics human action video dataset. arXiv preprint arXiv:1705.06950 (2017).  Will Kay Joao Carreira Karen Simonyan Brian Zhang Chloe Hillier Sudheendra Vijayanarasimhan Fabio Viola Tim Green Trevor Back Paul Natsev et al. 2017. The kinetics human action video dataset. arXiv preprint arXiv:1705.06950 (2017)."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587756"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350978"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123432"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"e_1_3_2_2_24_1","volume-title":"Proceedings of the 27th ACM International Conference on Multimedia (MM). ACM, 1777--1785","author":"Lokovc Jakub","year":"2019","unstructured":"Jakub Lokovc , Gregor Kovalvc ik, Tom\u00e1vs Souvc ek, Jaroslav Moravec , and Pvr emysl vC ech. 2019 . A framework for effective known-item search in video . In Proceedings of the 27th ACM International Conference on Multimedia (MM). ACM, 1777--1785 . Jakub Lokovc, Gregor Kovalvc ik, Tom\u00e1vs Souvc ek, Jaroslav Moravec, and Pvr emysl vC ech. 2019. A framework for effective known-item search in video. In Proceedings of the 27th ACM International Conference on Multimedia (MM). ACM, 1777--1785."},{"key":"e_1_3_2_2_25_1","volume-title":"Proc. ICLR","author":"Mishra Nikhil","year":"2018","unstructured":"Nikhil Mishra , Mostafa Rohaninejad , Xi Chen , and Pieter Abbeel . 2018 . A simple neural attentive meta-learner . Proc. ICLR (2018). Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel. 2018. A simple neural attentive meta-learner. Proc. ICLR (2018)."},{"key":"e_1_3_2_2_26_1","volume-title":"Online ensemble learning","author":"Oza Nikunj Chandrakant","unstructured":"Nikunj Chandrakant Oza and Stuart Russell . 2001. Online ensemble learning . University of California , Berkeley . Nikunj Chandrakant Oza and Stuart Russell. 2001. Online ensemble learning .University of California, Berkeley."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00408"},{"key":"e_1_3_2_2_28_1","volume-title":"Proc","author":"Qi Mengshi","unstructured":"Mengshi Qi , Jie Qin , Annan Li , Yunhong Wang , Jiebo Luo , and Luc Van Gool . 2018a. stagnet: An attentive semantic RNN for group activity recognition . In Proc . ECCV. Springer , 101--117. Mengshi Qi, Jie Qin, Annan Li, Yunhong Wang, Jiebo Luo, and Luc Van Gool. 2018a. stagnet: An attentive semantic RNN for group activity recognition. In Proc. ECCV. Springer, 101--117."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01275"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123311"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3265845.3265851"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2983567"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00538"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351058"},{"key":"e_1_3_2_2_35_1","volume-title":"Proc. ICLR.","author":"Ravi Sachin","year":"2017","unstructured":"Sachin Ravi and Hugo Larochelle . 2017 . Optimization as a model for few-shot learning . In Proc. ICLR. Sachin Ravi and Hugo Larochelle. 2017. Optimization as a model for few-shot learning. In Proc. ICLR."},{"key":"e_1_3_2_2_36_1","volume-title":"Proc. ICML. 1842--1850","author":"Santoro Adam","year":"2016","unstructured":"Adam Santoro , Sergey Bartunov , Matthew Botvinick , Daan Wierstra , and Timothy Lillicrap . 2016 . Meta-learning with memory-augmented neural networks . In Proc. ICML. 1842--1850 . Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap. 2016. Meta-learning with memory-augmented neural networks. In Proc. ICML. 1842--1850."},{"key":"e_1_3_2_2_37_1","volume-title":"Nonlinear estimation and classification","author":"Schapire Robert E","unstructured":"Robert E Schapire . 2003. The boosting approach to machine learning: An overview . In Nonlinear estimation and classification . Springer , 149--171. Robert E Schapire. 2003. The boosting approach to machine learning: An overview. In Nonlinear estimation and classification. Springer, 149--171."},{"key":"e_1_3_2_2_38_1","volume-title":"Improved boosting algorithms using confidence-rated predictions. Machine learning","author":"Schapire Robert E","year":"1999","unstructured":"Robert E Schapire and Yoram Singer . 1999. Improved boosting algorithms using confidence-rated predictions. Machine learning , Vol. 37 , 3 ( 1999 ), 297--336. Robert E Schapire and Yoram Singer. 1999. Improved boosting algorithms using confidence-rated predictions. Machine learning, Vol. 37, 3 (1999), 297--336."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123380"},{"key":"e_1_3_2_2_40_1","volume-title":"Proc","author":"Sigurdsson Gunnar A","unstructured":"Gunnar A Sigurdsson , G\u00fcl Varol , Xiaolong Wang , Ali Farhadi , Ivan Laptev , and Abhinav Gupta . 2016. Hollywood in homes: Crowdsourcing data collection for activity understanding . In Proc . ECCV. Springer , 510--526. Gunnar A Sigurdsson, G\u00fcl Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta. 2016. Hollywood in homes: Crowdsourcing data collection for activity understanding. In Proc. ECCV. Springer, 510--526."},{"key":"e_1_3_2_2_41_1","volume-title":"Proc. NIPS. 568--576","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . 2014 . Two-stream convolutional networks for action recognition in videos . In Proc. NIPS. 568--576 . Karen Simonyan and Andrew Zisserman. 2014. Two-stream convolutional networks for action recognition in videos. In Proc. NIPS. 568--576."},{"key":"e_1_3_2_2_42_1","volume-title":"Proc. NIPS. 4077--4087","author":"Snell Jake","year":"2017","unstructured":"Jake Snell , Kevin Swersky , and Richard Zemel . 2017 . Prototypical networks for few-shot learning . In Proc. NIPS. 4077--4087 . Jake Snell, Kevin Swersky, and Richard Zemel. 2017. Prototypical networks for few-shot learning. In Proc. NIPS. 4077--4087."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00651"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"e_1_3_2_2_46_1","volume-title":"Proc. NIPS. 3630--3638","author":"Vinyals Oriol","year":"2016","unstructured":"Oriol Vinyals , Charles Blundell , Timothy Lillicrap , Daan Wierstra , 2016 . Matching networks for one shot learning . In Proc. NIPS. 3630--3638 . Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al. 2016. Matching networks for one shot learning. In Proc. NIPS. 3630--3638."},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.441"},{"key":"e_1_3_2_2_48_1","volume-title":"Proc","author":"Wang Limin","unstructured":"Limin Wang , Yuanjun Xiong , Zhe Wang , Yu Qiao , Dahua Lin , Xiaoou Tang , and Luc Van Gool . 2016. Temporal segment networks: Towards good practices for deep action recognition . In Proc . ECCV. Springer , 20--36. Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool. 2016. Temporal segment networks: Towards good practices for deep action recognition. In Proc. ECCV. Springer, 20--36."},{"key":"e_1_3_2_2_49_1","volume-title":"Memory networks. arXiv preprint arXiv:1410.3916","author":"Weston Jason","year":"2014","unstructured":"Jason Weston , Sumit Chopra , and Antoine Bordes . 2014. Memory networks. arXiv preprint arXiv:1410.3916 ( 2014 ). Jason Weston, Sumit Chopra, and Antoine Bordes. 2014. Memory networks. arXiv preprint arXiv:1410.3916 (2014)."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350891"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299101"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351000"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240534"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2912290"},{"key":"e_1_3_2_2_55_1","volume-title":"Heng Tao Shen, and Ling Shao","author":"Zhang Zheng","year":"2018","unstructured":"Zheng Zhang , Li Liu , Fumin Shen , Heng Tao Shen, and Ling Shao . 2018 b. Binary multi-view clustering. IEEE transactions on pattern analysis and machine intelligence, Vol. 41 , 7 (2018), 1774--1782. Zheng Zhang, Li Liu, Fumin Shen, Heng Tao Shen, and Ling Shao. 2018b. Binary multi-view clustering. IEEE transactions on pattern analysis and machine intelligence, Vol. 41, 7 (2018), 1774--1782."},{"key":"e_1_3_2_2_56_1","volume-title":"Proc","author":"Zhu Linchao","unstructured":"Linchao Zhu and Yi Yang . 2018. Compound memory networks for few-shot video classification . In Proc . ECCV. Springer , 751--766. Linchao Zhu and Yi Yang. 2018. Compound memory networks for few-shot video classification. In Proc. ECCV. Springer, 751--766."},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350997"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","location":"Seattle WA USA","acronym":"MM '20","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3416269","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3416269","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:24Z","timestamp":1750197684000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3416269"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":57,"alternative-id":["10.1145\/3394171.3416269","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3416269","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}