Furniture-geek: Understanding fine-grained furniture attributes from freely associated text and tags

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Towards Open Set Deep Networks (2015, background): “Co-evolution of rich representations, scalable classification methods and large datasets have resulted in many commercial applications [5, 28, 16, 6].”
Towards Open World Recognition (2014, background): “Co-evolution of rich classification models along with advances in datasets have resulted in many commercial applications [8, 40, 29].”
Learning visual similarity for product design with convolutional neural networks (2015, unknown): “Whittle search uses relative attributes for product search [Parikh and Grauman 2011; Kovashka et al. 2012], Furnituregeek [Ordonez et al. 2014] understands fine-grained furniture attributes.”