Deep Learning for Automated Tagging of Fashion Images
- We present 9 deep learning classifiers to predict Fashion attributes in 4 different categories: apparel (dresses and tops), shoes, watches and luggages.
- By extracting these tags or attributes from fashion images, queries to the products catalogue can be generated looking for similar or complementary products, produce recommendations for the user, fill missing metadata, and overall provide an improved search experience
Tiered Deep Similarity Search for Fashion
- We propose a new attribute-guided metric learning (AGML) with multitask CNNs that jointly learns fashion attributes and image embeddings
FashionSearchNet: Fashion Search with Attribute Manipulation
- The focus of this paper is on retrieval of fashion images after manipulating attributes of the query images.
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