Scalable multi-class object detection

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Sparselet Models for Efficient Multiclass Object Detection (2012, background): “[11] builds a taxonomy of object classes based on shared features.”
Incremental Learning of Random Forests for Large-Scale Image Classification (2016, methodology): “RFs have been successfully used in many tasks such as image classification [23], vocabulary generation through vocabulary trees [24], as feature representation for image segmentation [25], object detection [26] and fine-grained image classification [12], [27].”
From categories to subcategories: Large-scale image classification with partial class label refinement (2015, background): “Moreover, each decision tree represents a hierarchy of classiﬁers such that the transfer of knowledge is implicitly effectuated [2].”
Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection (2013, methodology): “Object recognition is an area of active research in computer vision, and its performance has been improved substantially in recent years [6, 19, 9, 12, 4, 16].”