# Fashion-Gen: The Generative Fashion Dataset and Challenge

arXiv: https://arxiv.org/abs/1806.08317 · HTML: https://mlsanity.com/paper/1806.08317/

## Key facts

- Cited by 65 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2018.

## Built on by (most cited first, 30 of 65)

- [VLP: A Survey on Vision-Language Pre-training](https://mlsanity.com/paper/2202.09061/) (2022)
- [Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey](https://mlsanity.com/paper/2302.10035/) (2023)
- [Kaleido-BERT: Vision-Language Pre-training on Fashion Domain](https://mlsanity.com/paper/2103.16110/) (2021)
- [Towards Discovery and Attribution of Open-world GAN Generated Images](https://mlsanity.com/paper/2105.04580/) (2021)
- [Evaluation Gaps in Machine Learning Practice](https://mlsanity.com/paper/2205.05256/) (2022)
- [Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization](https://mlsanity.com/paper/2211.07394/) (2022)
- [Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation](https://mlsanity.com/paper/2502.08826/) (2025)
- [FAME-ViL: Multi-Tasking Vision-Language Model for Heterogeneous Fashion Tasks](https://mlsanity.com/paper/2303.02483/) (2023)
- [FashionViL: Fashion-Focused Vision-and-Language Representation Learning](https://mlsanity.com/paper/2207.08150/) (2022)
- [S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions](https://mlsanity.com/paper/2305.14095/) (2023)
- [Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback](https://mlsanity.com/paper/2106.04128/) (2021)
- [CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation](https://mlsanity.com/paper/2308.07146/) (2023)
- [Progressive Learning for Image Retrieval with Hybrid-Modality Queries](https://mlsanity.com/paper/2204.11212/) (2022)
- [CommerceMM: Large-Scale Commerce MultiModal Representation Learning with Omni Retrieval](https://mlsanity.com/paper/2202.07247/) (2022)
- [FICE: Text-Conditioned Fashion Image Editing With Guided GAN Inversion](https://mlsanity.com/paper/2301.02110/) (2023)
- [UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation](https://mlsanity.com/paper/2408.11305/) (2024)
- [CMA-CLIP: Cross-Modality Attention CLIP for Image-Text Classification](https://mlsanity.com/paper/2112.03562/) (2021)
- [Single-Stream Multi-Level Alignment for Vision-Language Pretraining](https://mlsanity.com/paper/2203.14395/) (2022)
- [Ethics and Creativity in Computer Vision](https://mlsanity.com/paper/2112.03111/) (2021)
- [Masked Vision-Language Transformer in Fashion](https://mlsanity.com/paper/2210.15110/) (2022)
- [FashionSAP: Symbols and Attributes Prompt for Fine-grained Fashion Vision-Language Pre-training](https://mlsanity.com/paper/2304.05051/) (2023)
- [Leveraging Large Language Models for Multimodal Search](https://mlsanity.com/paper/2404.15790/) (2024)
- [Test-time Adaptation for Cross-modal Retrieval with Query Shift](https://mlsanity.com/paper/2410.15624/) (2024)
- [OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data](https://mlsanity.com/paper/2309.05551/) (2023)
- [SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining](https://mlsanity.com/paper/2404.01156/) (2024)
- [FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning](https://mlsanity.com/paper/2210.15028/) (2022)
- [Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles](https://mlsanity.com/paper/2211.16504/) (2022)
- [Adapting Vision-Language Models Without Labels: A Comprehensive Survey](https://mlsanity.com/paper/2508.05547/) (2025)
- [MOON: Generative MLLM-based Multimodal Representation Learning for E-commerce Product Understanding](https://mlsanity.com/paper/2508.11999/) (2025)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)

## Abstract (arXiv)

We introduce a new dataset of 293,008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists. Each item is photographed from a variety of angles. We provide baseline results on 1) high-resolution image generation, and 2) image generation conditioned on the given text descriptions. We invite the community to improve upon these baselines. In this paper, we also outline the details of a challenge that we are launching based upon this dataset.