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https://github.com/ayushidalmia/awesome-fashion-ai

A repository to curate and summarise research papers related to fashion and e-commerce
https://github.com/ayushidalmia/awesome-fashion-ai
List: awesome-fashion-ai
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A repository to curate and summarise research papers related to fashion and e-commerce
Host: GitHub
URL: https://github.com/ayushidalmia/awesome-fashion-ai
Owner: ayushidalmia
Created: 2017-07-18T10:16:41.000Z (almost 7 years ago)
Default Branch: master
Last Pushed: 2021-11-12T18:29:30.000Z (over 2 years ago)
Last Synced: 2024-04-04T07:04:36.864Z (2 months ago)
Topics: awesome-list, awesome-lists, deeplearning, fashion, machine-learning, research-paper
Size: 67.4 KB
Stars: 1,125
Watchers: 87
Forks: 237
Open Issues: 2
Metadata Files:
- Readme: README.md
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awesome-virtual-try-on - awesome-fashion-ai
awesome-ai-list-guide - awesome-fashion-ai - commerce (Others)
awesome-artificial-intelligence - awesome-fashion-ai - A repository to curate and summarise research papers related to fashion and e-commerce. (Other awesome AI lists)
Cool-Fashion-Papers - [ayushidalmia/awesome-fashion-ai
ultimate-awesome - awesome-fashion-ai - A repository to curate and summarise research papers related to fashion and e-commerce. (Other Lists / Julia Lists)
README

        # awesome-fashion-ai

[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

A curated list of research papers, datasets, tools, conferences, workshops related to AI for fashion and e-commerce.

## Table of Contents

* [Papers](#papers)

* [Workshops](#workshops)

* [Tutorials](#tutorials)

* [Datasets](#datasets)

* [Miscellaneous](#miscellaneous)

### Papers

Areas

* [Fashion Embeddings](#fashion-embeddings)

* [Personalisation/Recommendation/Outfit Composition/Compatibility](#personalisationrecommendationoutfit-compositioncompatibility)

* [Visual Search/Visual Recommendation/Visual Retrieval](#visual-searchvisual-recommendationvisual-retrieval)

* [Natural Language Understanding in Fashion](#natural-language-understanding-in-fashion)

* [Fashion Image Object Detection/Classification/Parsing/Segmentation/Attribute Manipulation](#fashion-image-object-detectionclassificationparsingsegmentationattribute-manipulation)

* [Retail Insights/Trends/Forecasting/Inventory Management](#retail-insightstrendsforecastinginventory-management)

* [Image Generation/Image Manipulation in Fashion/Style Transfer](#image-generationimage-manipulation-in-fashionstyle-transfer)

* [Styling/Occasion](#stylingoccasion)

* [Social Media](#social-media)

* [Sizing/Virtual Trial Room](#sizingvirtual-trial-room)

* [Video](#video)

* [Multimodal](#multimodal)

* [Clothing Model](#clothing-model)

##### Fashion Embeddings

  - [Semi-Supervised Visual Representation Learning for Fashion Compatibility](https://arxiv.org/abs/2109.08052)  ACM RecSys 2021

  - [Fashion Style in 128 Floats: Joint Ranking and Classification using Weak Data for Feature Extraction](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Simo-Serra_Fashion_Style_in_CVPR_2016_paper.pdf)

  - [Learning Type-Aware Embeddings for Fashion Compatibility](https://arxiv.org/pdf/1803.09196v1.pdf), ECCV, 2018

  - [Style2Vec: Representation Learning for Fashion Items from Style Sets](https://arxiv.org/pdf/1708.04014v1.pdf)

  - [Context-Aware Visual Compatibility Prediction](https://arxiv.org/abs/1902.03646)

  

##### Personalisation/Recommendation/Outfit Composition/Compatibility

  - [Hi, magic closet, tell me what to wear!](https://people.cs.clemson.edu/~jzwang/1501863/mm2012/p619-liu.pdf), MM, 2012

  - [Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources](https://arxiv.org/pdf/1807.03235v1.pdf)

  - [Creating Capsule Wardrobes from Fashion Images](http://openaccess.thecvf.com/content_cvpr_2018/papers/Hsiao_Creating_Capsule_Wardrobes_CVPR_2018_paper.pdf)

  - [Neuroaesthetics in Fashion: Modeling the Perception of Fashionability](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Simo-Serra_Neuroaesthetics_in_Fashion_2015_CVPR_paper.pdf)

  - [Interpretable Partitioned Embedding for Customized Fashion Outfit Composition](https://arxiv.org/pdf/1806.04845v4.pdf)

  - [Visually-Aware Fashion Recommendation and Design with Generative Image Models](https://arxiv.org/pdf/1711.02231v1.pdf)

  - [An LSTM-Based Dynamic Customer Model for Fashion Recommendation](https://arxiv.org/pdf/1708.07347v1.pdf)

  - [Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products](https://arxiv.org/pdf/1803.07679v1.pdf)

  - [Mining Fashion Outfit Composition Using An End-to-End Deep Learning Approach on Set Data](https://arxiv.org/pdf/1608.03016v2.pdf)

  - [Learning Fashion Compatibility with Bidirectional LSTMs](https://arxiv.org/pdf/1707.05691v1.pdf)

  - [Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences](https://arxiv.org/pdf/1509.07473v1.pdf)

  - [Recommending Outfits from Personal Closet](https://arxiv.org/pdf/1804.09979v1.pdf)

  - [Toward Explainable Fashion Recommendation](https://arxiv.org/pdf/1901.04870v1.pdf) 

  

##### Visual Search/Visual Recommendation/Visual Retrieval

  - [Studio2Shop: from studio photo shoots to fashion articles](https://arxiv.org/pdf/1807.00556v1.pdf)

  - [Learning Attribute Representations with Localization for Flexible Fashion Search](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ak_Learning_Attribute_Representations_CVPR_2018_paper.pdf)

  - [Learning the Latent “Look”: Unsupervised Discovery of a Style-Coherent Embedding from Fashion Images](https://arxiv.org/pdf/1707.03376v2.pdf)

  - [Automatic Spatially-aware Fashion Concept Discovery](https://arxiv.org/pdf/1708.01311v1.pdf)

  - [Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction](https://arxiv.org/pdf/1709.09426v1.pdf)

  - [Large Scale Visual Recommendations From Street Fashion Images](https://arxiv.org/pdf/1401.1778v1.pdf)

  - [Learning Unified Embedding for Apparel Recognition](https://arxiv.org/pdf/1707.05929.pdf)

  - [Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce](https://arxiv.org/pdf/1703.02344v1.pdf)

  - [Visual Search at eBay](https://arxiv.org/pdf/1706.03154v2.pdf)

  - [Visually-Aware Fashion Recommendation and Design with Generative Image Models](https://arxiv.org/pdf/1711.02231v1.pdf)

  - [Cross-domain Image Retrieval with a Dual Attribute-aware Ranking Network](https://arxiv.org/pdf/1505.07922v1.pdf)

  - [Image-based Recommendations on Styles and Substitutes](https://arxiv.org/pdf/1506.04757v1.pdf)

  - [Runway to Realway: Visual Analysis of Fashion](http://www.tamaraberg.com/papers/runway_to_realway.pdf)

  - [Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos](http://image.ntua.gr/iva/files/kalantidis_icmr13.pdf), ICMR 2013

  - [DeepStyle: Multimodal Search Engine for Fashion and Interior Design](https://arxiv.org/abs/1801.03002v2)

##### Natural Language Understanding in Fashion

  - [A Hierarchical Deep Learning Natural Language Parser for Fashion](https://arxiv.org/pdf/1806.09511v1.pdf)

  - ["Let me convince you to buy my product ... ": A Case Study of an Automated Persuasive System for Fashion Products](https://arxiv.org/pdf/1709.08366v1.pdf)

  - ["Designing the Future of Personal Fashion"](http://ranjithakumar.net/resources/personal_fashion.pdf)

  - [Deep Recurrent Neural Networks for Product Attribute Extraction in eCommerce](https://arxiv.org/pdf/1803.11284v1.pdf)

  

##### Fashion Image Object Detection/Classification/Parsing/Segmentation/Attribute Manipulation/Landmark Detection

  - [How To Extract Fashion Trends From Social Media?](https://arxiv.org/pdf/1806.10787v1.pdf)

  - [Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Attentive_Fashion_Grammar_CVPR_2018_paper.pdf)

  - [Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search](http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhao_Memory-Augmented_Attribute_Manipulation_CVPR_2017_paper.pdf)

  - [DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations](https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Liu_DeepFashion_Powering_Robust_CVPR_2016_paper.pdf)

  - [A Unified Model with Structured Output for Fashion Images Classification](https://arxiv.org/pdf/1806.09445v1.pdf)

  - [Product Characterisation towards Personalisation](https://arxiv.org/pdf/1803.07679v1.pdf)

  - [Fusing Hierarchical Convolutional Features for Human Body Segmentation and Clothing Fashion Classification](https://arxiv.org/pdf/1803.03415v2.pdf)

  - [How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning](https://arxiv.org/pdf/1806.10787v1.pdf)

  - [Unconstrained Fashion Landmark Detection via Hierarchical Recurrent Transformer Networks](https://arxiv.org/pdf/1708.02044v1.pdf)

  - [Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors](https://arxiv.org/pdf/1411.5319v2.pdf)

  - [Parsing Clothing in Fashion Photographs](http://www.tamaraberg.com/papers/parsingclothing.pdf)

  - [Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items](http://www.tamaraberg.com/papers/paperdoll.pdf)

  - [Two-Stream Multi-Task Network for Fashion Recognition](https://arxiv.org/abs/1901.10172v2)

  - [Spatial-Aware Non-Local Attention for Fashion Landmark Detection](https://arxiv.org/abs/1903.04104v1)

  - [Semantic Segmentation of Fashion Images Using Feature Pyramid Networks](http://openaccess.thecvf.com/content_ICCVW_2019/html/CVFAD/Martinsson_Semantic_Segmentation_of_Fashion_Images_Using_Feature_Pyramid_Networks_ICCVW_2019_paper.html)

  

##### Retail Insights/Trends/Forecasting/Inventory Management

  - [FashionBrain Project: A Vision for Understanding Europe’s Fashion Data Universe](https://arxiv.org/pdf/1710.09788v1.pdf)

  - [Fashion Forward: Forecasting Visual Style in Fashion](https://arxiv.org/pdf/1705.06394v2.pdf)

  - [When Fashion Meets Big Data: Discriminative Mining of Best Selling Clothing Features](https://arxiv.org/pdf/1611.03915v2.pdf)

  - [Towards Predicting the Likeability of Fashion Images](https://arxiv.org/pdf/1511.05296v2.pdf)

  - [Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study](https://arxiv.org/pdf/1608.07444v1.pdf)

  - [Robust Order Scheduling in the Fashion Industry: A Multi-Objective Optimization Approach](https://arxiv.org/pdf/1702.00159v1.pdf)

  - [Changing Fashion Culture](https://arxiv.org/pdf/1703.07920v1.pdf)

  - [Sales Potential: Modelling Sellability of Visual Aesthetics of a Fashion Product](https://kddfashion2017.mybluemix.net/final_submissions/ML4Fashion_paper_10.pdf)

  - [ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting](https://arxiv.org/pdf/1803.03800.pdf)

  

##### Image Generation/Image Manipulation in Fashion/Style Transfer

  - [Joint Discriminative and Generative Learning for Person Re-identification](https://arxiv.org/abs/1904.07223), CVPR 2019 [[Project]](http://zdzheng.xyz/DG-Net/) [[Paper]](https://arxiv.org/abs/1904.07223) [[YouTube]](https://www.youtube.com/watch?v=ubCrEAIpQs4) [[Bilibili]](https://www.bilibili.com/video/av51439240) [[Poster]](http://zdzheng.xyz/images/DGNet_poster.pdf)

  - [The Conditional Analogy GAN: Swapping Fashion Articles on People Images](https://arxiv.org/pdf/1709.04695v1.pdf)

  - [Language Guided Fashion Image Manipulation with Feature-wise Transformations](https://arxiv.org/pdf/1808.04000v1.pdf)

  - [SwapNet: Image Based Garment Transfer](http://openaccess.thecvf.com/content_ECCV_2018/papers/Amit_Raj_SwapNet_Garment_Transfer_ECCV_2018_paper.pdf), ECCV 2018

  - [Compatible and Diverse Fashion Image Inpainting](https://arxiv.org/abs/1902.01096v1)

  - [Fashion++: Minimal Edits for Outfit Improvement](https://arxiv.org/abs/1904.09261)

  - [Generative Modelling of Semantic Segmentation Data in the Fashion Domain](http://openaccess.thecvf.com/content_ICCVW_2019/html/CVFAD/Korneliusson_Generative_Modelling_of_Semantic_Segmentation_Data_in_the_Fashion_Domain_ICCVW_2019_paper.html)

##### Styling/Occasion

  - [Hipster Wars: Discovering Elements of Fashion Styles](http://www.tamaraberg.com/papers/hipster_eccv14.pdf)

  

##### Social Media

  - [Chic or Social: Visual Popularity Analysis in OnlineFashion Networks](http://www.tamaraberg.com/papers/kota_acm14.pdf)

  - [Identifying Fashion Accounts in Social Networks](https://kddfashion2017.mybluemix.net/final_submissions/ML4Fashion_paper_21.pdf)

  

##### Sizing/Virtual Trial Room

  - [Decomposing Fit Semantics for Product Size Recommendation in Metric Spaces](https://cseweb.ucsd.edu/~m5wan/paper/recsys18_rmisra)

  - [M2E-Try On Net: Fashion from Model to Everyone](https://arxiv.org/pdf/1811.08599v1.pdf)

  

##### Video

  - [Dress like a Star: Retrieving Fashion Products from Videos](https://arxiv.org/pdf/1710.07198v1.pdf)

  - [Video2Shop: Exactly Matching Clothes in Videos to Online Shopping Images](https://arxiv.org/abs/1804.05287v1), CVPR, 2017

##### Multimodal

  - [DeepStyle: Multimodal Search Engine for Fashion and Interior Design](https://arxiv.org/pdf/1801.03002v1.pdf)

 

##### Dialog/Conversation

  - [Netizen-Style Commenting on Fashion Photos: Dataset and Diversity Measures](https://arxiv.org/pdf/1801.10300v1.pdf)

  - [Fashion Conversation Data on Instagram](https://arxiv.org/pdf/1704.04137.pdf)

  

##### Clothing Model

  - [DeepWrinkles: Accurate and Realistic Clothing Modeling](http://openaccess.thecvf.com/content_ECCV_2018/papers/Zorah_Laehner_DeepWrinkles_Accurate_and_ECCV_2018_paper.pdf), ECCV 2018

  - [Learning a Shared Shape Space for Multimodal Garment Design](https://geometry.cs.ucl.ac.uk/projects/2018/garment_design/), SIGGRAPH Asia 2018

  - [Garnet: A Two-stream Network for Fast and Accurate 3D Cloth Draping](https://www.epfl.ch/labs/cvlab/research/garment-simulation/garnet/), ICCV 2019

  - [Learning-Based Animation of Clothing for Virtual Try-On](http://dancasas.github.io/projects/LearningBasedVirtualTryOn/), Eurographics 2019

  - [TailorNet :Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style](https://virtualhumans.mpi-inf.mpg.de/tailornet/), CVPR 2020

  - [SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing](https://virtualhumans.mpi-inf.mpg.de/sizer/), ECCV 2020

 

##### 3D Clothing from Images

  - [MULTI-GARMENT NET: LEARNING TO DRESS 3D PEOPLE FROM IMAGES](https://virtualhumans.mpi-inf.mpg.de/mgn/), ICCV 2019

  - [Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images](https://kv2000.github.io/2020/03/25/deepFashion3DRevisited/), ECCV 2020 

  - [BCNet: Learning Body and Cloth Shape from A Single Image](https://arxiv.org/abs/2004.00214), ECCV 2020

### Workshops

* KDD Workshop on AI for Fashion  [2020](https://kddfashion2020.mybluemix.net/), [2019](https://kddfashion2019.mybluemix.net/), [2018](https://kddfashion2018.mybluemix.net/), [2017](https://kddfashion2017.mybluemix.net/), [2016](http://kddfashion2016.mybluemix.net/)

* ICCV/ECCV Workshop on Computer Vision for Fashion, Art and Design [2020](https://sites.google.com/view/cvcreative2020), [2019](https://sites.google.com/view/cvcreative) [2018](https://sites.google.com/view/eccvfashion/), [2017](https://sites.google.com/zalando.de/cvf-iccv2017/home?authuser=0)

* SIGIR Workshop On eCommerce [2018](https://sigir-ecom.github.io/index.html), [2017](http://sigir-ecom.weebly.com/)

* Recommender Systems in Fashion [2020](https://fashionxrecsys.github.io/fashionxrecsys-2020/),  [2019](https://zalandoresearch.github.io/fashionxrecsys/)

### Tutorials

* [Concept to Code: Deep Learning for Fashion Recommendation.](https://www2019.thewebconf.org/tutorials).        

Organizers: Omprakash Sonie, Muthusamy Chelliah and Shamik Sural, The Web Conference, 2019

### Datasets

* [Large-scale Fashion (DeepFashion)](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion.html)

* [Street2Shop](http://www.tamaraberg.com/street2shop/)

* [Fashionista](http://vision.is.tohoku.ac.jp/~kyamagu/research/clothing_parsing/)

* [Paperdoll](http://vision.is.tohoku.ac.jp/~kyamagu/research/paperdoll/)

* [Fashion MNIST](https://github.com/zalandoresearch/fashion-mnist)

* [Fashion Takes Shape](https://www.groundai.com/project/fashion-is-taking-shape-understanding-clothing-preference-based-on-body-shape-from-online-sources/1)

* [ModaNet](https://github.com/eBay/modanet) [paper](https://arxiv.org/pdf/1807.01394v2.pdf)

* [DeepFashion2](https://github.com/switchablenorms/DeepFashion2),[paper](https://arxiv.org/abs/1901.07973)

* [iMaterialist-Fashion](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6)

* [Clothing Fit Dataset for Size Recommendation](https://www.kaggle.com/rmisra/clothing-fit-dataset-for-size-recommendation)

* [MULTI-GARMENT NET: LEARNING TO DRESS 3D PEOPLE FROM IMAGES](https://virtualhumans.mpi-inf.mpg.de/mgn/), ICCV 2019

* [TailorNet: Predicting Garment in 3D as a Function of Human Pose, Shape and Garment Style](https://virtualhumans.mpi-inf.mpg.de/tailornet/), CVPR 2020

* [Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images](https://kv2000.github.io/2020/03/25/deepFashion3DRevisited/), ECCV 2020

* [SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing](https://virtualhumans.mpi-inf.mpg.de/sizer/), ECCV 2020

### Miscellaneous

- [Fashion-Gen: The Generative Fashion Dataset and Challenge](https://arxiv.org/abs/1806.08317v1)

- [Brand > Logo: Visual Analysis of Fashion Brands](https://arxiv.org/pdf/1810.09941v1.pdf)

### Author

[Ayushi Dalmia](https://github.com/ayushidalmia)

###License

MIT