Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification

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Few-Shot Class-Incremental Learning (2020, background): “Convolutional Neural Networks (CNNs) have been successfully applied to a broad range of computer vision tasks [17, 11, 34, 4, 22, 25, 45, 19].”
Bi-Objective Continual Learning: Learning 'New' While Consolidating 'Known' (2020, background): “…(Krizhevsky, Sutskever, and Hinton 2012; He et al. 2015; Wang et al. 2010; Ren et al. 2015; Redmon et al. 2015; Cheng et al. 2016; Shun et al. 2016; Long, Shelhamer, and Darrell 2015; Chen et al. 2017; Liu et al. 2017; Deng et al. 2018; Tusng-Yu, Aruni, and Subhransu 2015; Wei et al. 2018a; 2018b).”
Fine-Grained Image Analysis With Deep Learning: A Survey (2021, methodology): “3% GP [104] ECCV 2018 VGG-16 448× 448 85.”
See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification (2019, unknown): “4 GP-256 [31] 85.”
Bayesian Loss for Crowd Count Estimation With Point Supervision (2019, background): “In overcrowded scenes, clutters and severe occlusions make it unfeasible to detect every single person, despite the progresses in related fields [19, 10, 47, 17, 33, 43, 61, 50, 48, 34, 49, 55, 60, 52].”