# Creating Capsule Wardrobes from Fashion Images

arXiv: https://arxiv.org/abs/1712.02662 · HTML: https://mlsanity.com/paper/1712.02662/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Dec 2017.

## Built on by (most cited first, 24 of 24)

- [LaDI-VTON: Latent Diffusion Textual-Inversion Enhanced Virtual Try-On](https://mlsanity.com/paper/2305.13501/) (2023)
- [Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing](https://mlsanity.com/paper/2304.02051/) (2023)
- [Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback](https://mlsanity.com/paper/2106.04128/) (2021)
- [OutfitTransformer: Learning Outfit Representations for Fashion Recommendation](https://mlsanity.com/paper/2204.04812/) (2022)
- [GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting](https://mlsanity.com/paper/2405.07472/) (2024)
- [ITA-MDT: Image-Timestep-Adaptive Masked Diffusion Transformer Framework for Image-Based Virtual Try-On](https://mlsanity.com/paper/2503.20418/) (2025)
- [OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data](https://mlsanity.com/paper/2309.05551/) (2023)
- [DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning](https://mlsanity.com/paper/2201.13357/) (2022)
- [From Culture to Clothing: Discovering the World Events Behind A Century of Fashion Images](https://mlsanity.com/paper/2102.01690/) (2021)
- [3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes](https://mlsanity.com/paper/2410.11133/) (2024)
- [Multimodal-Conditioned Latent Diffusion Models for Fashion Image Editing](https://mlsanity.com/paper/2403.14828/) (2024)
- [Exploring AI in Fashion: A Review of Aesthetics, Personalization, Virtual Try-On, and Forecasting](https://mlsanity.com/paper/2101.08301/) (2021)
- [I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion](https://mlsanity.com/paper/2102.08871/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation](https://mlsanity.com/paper/2111.14145/) (2021)
- [Imitation Learning for Fashion Style Based on Hierarchical Multimodal Representation](https://mlsanity.com/paper/2004.06229/) (2020)
- [Unified Simulation, Perception, and Generation of Human Behavior](https://mlsanity.com/paper/2204.13678/) (2022)
- [Learning Fashion Compatibility from In-the-wild Images](https://mlsanity.com/paper/2206.05982/) (2022)
- [Partial Visual-Semantic Embedding: Fashion Intelligence System with Sensitive Part-by-Part Learning](https://mlsanity.com/paper/2211.06688/) (2022)
- [Fashionpedia-Taste: A Dataset towards Explaining Human Fashion Taste](https://mlsanity.com/paper/2305.02307/) (2023)
- [Fashionpedia-Ads: Do Your Favorite Advertisements Reveal Your Fashion Taste?](https://mlsanity.com/paper/2305.02360/) (2023)
- [ICAR: Image-based Complementary Auto Reasoning](https://mlsanity.com/paper/2308.09119/) (2023)
- [FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On](https://mlsanity.com/paper/2606.29319/) (2026)
- [Explaining Image Similarity with Automatically Extracted Concept Activation Vectors](https://mlsanity.com/paper/2607.28386/) (2026)

## Abstract (arXiv)

We propose to automatically create capsule wardrobes. Given an inventory of candidate garments and accessories, the algorithm must assemble a minimal set of items that provides maximal mix-and-match outfits. We pose the task as a subset selection problem. To permit efficient subset selection over the space of all outfit combinations, we develop submodular objective functions capturing the key ingredients of visual compatibility, versatility, and user-specific preference. Since adding garments to a capsule only expands its possible outfits, we devise an iterative approach to allow near-optimal submodular function maximization. Finally, we present an unsupervised approach to learn visual compatibility from "in the wild" full body outfit photos; the compatibility metric translates well to cleaner catalog photos and improves over existing methods. Our results on thousands of pieces from popular fashion websites show that automatic capsule creation has potential to mimic skilled fashionistas in assembling flexible wardrobes, while being significantly more scalable.