# Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences

arXiv: https://arxiv.org/abs/1509.07473 · HTML: https://mlsanity.com/paper/1509.07473/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2015.

## Built on by (most cited first, 30 of 33)

- [Mining Latent Structures for Multimedia Recommendation](https://mlsanity.com/paper/2104.09036/) (2021)
- [OutfitTransformer: Learning Outfit Representations for Fashion Recommendation](https://mlsanity.com/paper/2204.04812/) (2022)
- [Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation](https://mlsanity.com/paper/2111.00678/) (2021)
- [Fine-Grained Fashion Similarity Prediction by Attribute-Specific Embedding Learning](https://mlsanity.com/paper/2104.02429/) (2021)
- [Effectively Leveraging Attributes for Visual Similarity](https://mlsanity.com/paper/2105.01695/) (2021)
- [From Culture to Clothing: Discovering the World Events Behind A Century of Fashion Images](https://mlsanity.com/paper/2102.01690/) (2021)
- [Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion](https://mlsanity.com/paper/2312.15826/) (2023)
- [Exploring AI in Fashion: A Review of Aesthetics, Personalization, Virtual Try-On, and Forecasting](https://mlsanity.com/paper/2101.08301/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Arbitrary Virtual Try-On Network: Characteristics Preservation and Trade-off between Body and Clothing](https://mlsanity.com/paper/2111.12346/) (2021)
- [Learning to Synthesize Compatible Fashion Items Using Semantic Alignment and Collocation Classification: An Outfit Generation Framework](https://mlsanity.com/paper/2502.06827/) (2025)
- [Learning Personal Style from Few Examples](https://mlsanity.com/paper/2105.14457/) (2021)
- [Transformer-based Graph Neural Networks for Outfit Generation](https://mlsanity.com/paper/2304.08098/) (2023)
- [Progressive Limb-Aware Virtual Try-On](https://mlsanity.com/paper/2503.12588/) (2025)
- [Attribute-aware Explainable Complementary Clothing Recommendation](https://mlsanity.com/paper/2107.01655/) (2021)
- [FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation](https://mlsanity.com/paper/2111.14145/) (2021)
- [COutfitGAN: Learning to Synthesize Compatible Outfits Supervised by Silhouette Masks and Fashion Styles](https://mlsanity.com/paper/2502.08674/) (2025)
- [Hybrid-Hierarchical Fashion Graph Attention Network for Compatibility-Oriented and Personalized Outfit Recommendation](https://mlsanity.com/paper/2508.11105/) (2025)
- [Unimodal vs. Multimodal Siamese Networks for Outfit Completion](https://mlsanity.com/paper/2207.10355/) (2022)
- [VICTOR: Visual Incompatibility Detection with Transformers and Fashion-specific contrastive pre-training](https://mlsanity.com/paper/2207.13458/) (2022)
- [VISHIEN-MAAT: Scrollytelling visualization design for explaining Siamese Neural Network concept to non-technical users](https://mlsanity.com/paper/2304.03288/) (2023)
- [Lost Your Style? Navigating with Semantic-Level Approach for Text-to-Outfit Retrieval](https://mlsanity.com/paper/2311.02122/) (2023)
- [Character-based Outfit Generation with Vision-augmented Style Extraction via LLMs](https://mlsanity.com/paper/2402.05941/) (2024)
- [Fashion Recommendation: Outfit Compatibility using GNN](https://mlsanity.com/paper/2404.18040/) (2024)
- [Integrating Domain Knowledge into Large Language Models for Enhanced Fashion Recommendations](https://mlsanity.com/paper/2502.15696/) (2025)
- [Imitation Learning for Fashion Style Based on Hierarchical Multimodal Representation](https://mlsanity.com/paper/2004.06229/) (2020)
- [Outfit Generation and Recommendation -- An Experimental Study](https://mlsanity.com/paper/2211.16353/) (2022)
- [ICAR: Image-based Complementary Auto Reasoning](https://mlsanity.com/paper/2308.09119/) (2023)
- [BC-GAN: A Generative Adversarial Network for Synthesizing a Batch of Collocated Clothing](https://mlsanity.com/paper/2502.01080/) (2025)
- [Visual Product Graph: Bridging Visual Products And Composite Images For End-to-End Style Recommendations](https://mlsanity.com/paper/2505.21454/) (2025)

## Abstract (arXiv)

With the rapid proliferation of smart mobile devices, users now take millions of photos every day. These include large numbers of clothing and accessory images. We would like to answer questions like `What outfit goes well with this pair of shoes?' To answer these types of questions, one has to go beyond learning visual similarity and learn a visual notion of compatibility across categories. In this paper, we propose a novel learning framework to help answer these types of questions. The main idea of this framework is to learn a feature transformation from images of items into a latent space that expresses compatibility. For the feature transformation, we use a Siamese Convolutional Neural Network (CNN) architecture, where training examples are pairs of items that are either compatible or incompatible. We model compatibility based on co-occurrence in large-scale user behavior data; in particular co-purchase data from Amazon.com. To learn cross-category fit, we introduce a strategic method to sample training data, where pairs of items are heterogeneous dyads, i.e., the two elements of a pair belong to different high-level categories. While this approach is applicable to a wide variety of settings, we focus on the representative problem of learning compatible clothing style. Our results indicate that the proposed framework is capable of learning semantic information about visual style and is able to generate outfits of clothes, with items from different categories, that go well together.