Fashion and Apparel Classification using Convolutional Neural Networks
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Abstract (arXiv)
We present an empirical study of applying deep Convolutional Neural Networks (CNN) to the task of fashion and apparel image classification to improve meta-data enrichment of e-commerce applications. Five different CNN architectures were analyzed using clean and pre-trained models. The models were evaluated in three different tasks person detection, product and gender classification, on two small and large scale datasets.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Nov 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 2.
3 papers.
- 2021Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industrycited by 4
- 2025Hybrid-Hierarchical Fashion Graph Attention Network for Compatibility-Oriented and Personalized Outfit Recommendationcited by 2
- 2025African Gender Classification Using Clothing Identification Via Deep Learningcited by 0
- 2025Hybrid-Hierarchical Fashion Graph Attention Network for Compatibility-Oriented and Personalized Outfit Recommendation14 Aug 2025
- 2025African Gender Classification Using Clothing Identification Via Deep Learning26 Feb 2025
- 2021Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry28 Oct 2021