Style Finder: Fine-Grained Clothing Style Detection and Retrieval

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Image-Based Recommendations on Styles and Substitutes (2015, background): “04 75 7v 1 [ cs .”
Fine-Grained Image Classification by Exploring Bipartite-Graph Labels (2015, background): “Fine-grained image classification concerns the task of distinguishing sub-ordinate categories of some base classes such as dogs [26, 43], birds [5, 8], flowers [1, 40], plants [32, 45], cars [30, 36, 48], food [3, 6, 38, 59], clothes [14], fonts [10] and furniture [4].”
DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations (2016, methodology): “Recently, extensive research efforts have been devoted to clothes classification [11, 1, 29], attribute prediction [3, 13, 4, 24], and clothing item retrieval [17, 6, 10, 27, 15], because of their potential values to the industry.”
Style in the long tail: discovering unique interests with latent variable models in large scale social E-commerce (2014, background): “al [7] seeks to match similar styles of clothing with a combination of crowd-sourced tags and bag-of-words image features.”
Fashion Landmark Detection in the Wild (2016, background): “Visual fashion analysis has drawn lots of attentions recently, due to its wide spectrum of applications such as clothes recognition [1,2,3], retrieval [4,5,3], and recommendation [6,7].”