fashion_retrieval.md

• paper doll
  • has dataset
  • KNN
• Creating Capsule Wardrobes from Fashion Images
• Learning Fashion Compatibility with Bidirectional LSTMs
• Parsing Clothing in Fashion Photographs
  • we provide a large novel dataset and tools
• https://github.com/ihciah/deep-fashion-retrieval
• https://github.com/wenxinxu/deep-shopping
• https://github.com/leekyungmoon/WatchOUT
  • This project tried to combine two models for object detection and image retrieval. Specifically, Faster R-CNN and Triplet-Network using Inception were used. For a query image, it tries to detect the target clothes, optionally crop the image to focus on the target clothes and retrieve similar images.
• Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction
  • We achieve nearly state-of-art results on the DeepFashion In-Shop Clothes Retrieval and Categories Attributes Prediction [12] tasks, without using the provided training set.
• Deep Image Retrieval: Learning global representations for image search
• wayfair
  • https://tech.wayfair.com/2017/06/visual-search-with-deep-learning/
    • two outputs, an embedding vector for the latent space and product-type classification probabilities for known product categories
    • A query image is pushed through the network to get embedding and classification scores. Highly probabilistic class predictions restrict the search space and a subset of binary trees are searched for nearest neighbors of the embedding.
    • Dimensionality Reduction by Learning an Invariant Mapping
  • https://tech.wayfair.com/2018/05/object-detection-and-visual-search-improvements/
    • Object Detection: We used a set of 130,000 training images with 557,000 tagged objects and 37 unique classes, which was available to us as a result of an internal effort to tag the products in all of our imagery.
  • https://tech.wayfair.com/2018/05/the-duplicate-review-tool-incorporating-visual-search-into-merchandising-operations/
    • the algorithm also compares product images–the embeddings of top-ranked product images from Wayfair’s visual search algorithm are compared with a simple cosine similarity.
• Dimensionality Reduction by Learning an Invariant Mapping
• griddynamics
  • https://blog.griddynamics.com/expanding-product-search-with-image-similarity/
  • https://blog.griddynamics.com/reverse-image-search-with-convolutional-neural-networks/
• https://github.com/paucarre/tiefvision
• https://github.com/figitaki/deep-retrieval