Multiple/Single-View Human Action Recognition via Part-Induced Multitask Structural Learning

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RGB-D-based action recognition datasets: A survey (2016, methodology): “Multiview 3D Event [45] 4DHOI [45] 87 C, D, S Not given Multi-View TJU [49] MTSLþLL/ML [49] 1.”
Human Action Recognition From Various Data Modalities: A Review (2020, unknown): “Dataset Reference Year Modality #Class #Subject #Sample #View KTH [402] 2004 RGB 6 25 2,391 1 Weizmann [66] 2005 RGB 10 9 90 1 IXMAS [70] 2006 RGB 11 10 330 5 HDM05 [403] 2007 RGB,S 130 5 2,337 1 Hollywood [87] 2008 RGB 8 430 Hollywood2 [404] 2009 RGB 12 - 3,669 MSR-Action3D [254] 2010 S,D 20 10 567”
Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition (2017, methodology): “In contrast to the current methods that either consider all tasks as being related [1] [2] or heuristically impose explicit relationships among tasks [7], we focus on the automated exploration of the action grouping information to induce action modeling among the TABLE 1: Notations and Definitions N”
Deep multi-view learning methods: A review (2021, background): “MVTJU[211] Video 2 22 3,520 2015 Each action was performed 4 times by 20 subjects under two lighting conditions (i.”