# Leveraging Weakly Annotated Data for Fashion Image Retrieval and Label Prediction

arXiv: https://arxiv.org/abs/1709.09426 · HTML: https://mlsanity.com/paper/1709.09426/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2017.

## Built on by (most cited first, 19 of 19)

- [FINE Samples for Learning with Noisy Labels](https://mlsanity.com/paper/2102.11628/) (2021)
- [Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining](https://mlsanity.com/paper/2107.14572/) (2021)
- [M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining](https://mlsanity.com/paper/2109.04275/) (2021)
- [Limb-Aware Virtual Try-On Network with Progressive Clothing Warping](https://mlsanity.com/paper/2503.14074/) (2025)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Training with Product Digital Twins for AutoRetail Checkout](https://mlsanity.com/paper/2308.09708/) (2023)
- [Large Scale Long-tailed Product Recognition System at Alibaba](https://mlsanity.com/paper/2102.04652/) (2021)
- [Enhancing Fine-Grained Classification for Low Resolution Images](https://mlsanity.com/paper/2105.00241/) (2021)
- [Cross-Domain Product Representation Learning for Rich-Content E-Commerce](https://mlsanity.com/paper/2308.05550/) (2023)
- [Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond](https://mlsanity.com/paper/2308.14753/) (2023)
- [Progressive Limb-Aware Virtual Try-On](https://mlsanity.com/paper/2503.12588/) (2025)
- [FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation](https://mlsanity.com/paper/2111.14145/) (2021)
- [Deep Image Retrieval is not Robust to Label Noise](https://mlsanity.com/paper/2205.11195/) (2022)
- [Entity-Graph Enhanced Cross-Modal Pretraining for Instance-level Product Retrieval](https://mlsanity.com/paper/2206.08842/) (2022)
- [Automated System for Ship Detection from Medium Resolution Satellite Optical Imagery](https://mlsanity.com/paper/2104.13923/) (2021)
- [AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method](https://mlsanity.com/paper/2311.09624/) (2023)
- [Technologies for AI-Driven Fashion Social Networking Service with E-Commerce](https://mlsanity.com/paper/2203.10996/) (2022)
- [Design-time Fashion Popularity Forecasting in VR Environments](https://mlsanity.com/paper/2212.07187/) (2022)
- [Content-based jewellery item retrieval using the local region-based histograms](https://mlsanity.com/paper/2305.07540/) (2023)

## Abstract (arXiv)

In this paper, we present a method to learn a visual representation adapted for e-commerce products. Based on weakly supervised learning, our model learns from noisy datasets crawled on e-commerce website catalogs and does not require any manual labeling. We show that our representation can be used for downward classification tasks over clothing categories with different levels of granularity. We also demonstrate that the learnt representation is suitable for image retrieval. We achieve nearly state-of-art results on the DeepFashion In-Shop Clothes Retrieval and Categories Attributes Prediction tasks, without using the provided training set.