From Pixels to Posts: Retrieval-Augmented Fashion Captioning and Hashtag Generation

Moazzam Umer Gondal; Hamad Ul Qudous; Daniya Siddiqui; Asma Ahmad Farhan

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arXiv · 2511.19149

From Pixels to Posts: Retrieval-Augmented Fashion Captioning and Hashtag Generation

Moazzam Umer Gondal·Hamad Ul Qudous·Daniya Siddiqui·Asma Ahmad Farhan

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Abstract

This paper introduces the retrieval-augmented framework for automatic fashion caption and hashtag generation, combining multi-garment detection, attribute reasoning, and Large Language Model (LLM) prompting. The system aims to produce visually grounded, descriptive, and stylistically interesting text for fashion imagery, overcoming the limitations of end-to-end captioners that have problems with attribute fidelity and domain generalization. The pipeline combines a YOLO-based detector for multi-garment localization, k-means clustering for dominant color extraction, and a CLIP-FAISS retrieval module for fabric and gender attribute inference based on a structured product index. These attributes, together with retrieved style examples, create a factual evidence pack that is used to guide an LLM to generate human-like captions and contextually rich hashtags. A fine-tuned BLIP model is used as a supervised baseline model for comparison. Experimental results show that the YOLO detector is able to obtain a mean Average Precision (mAP@0.5) of 0.71 for nine categories of garments. The RAG-LLM pipeline generates expressive attribute-aligned captions and achieves mean attribute coverage of 0.80 with full coverage at the 50% threshold in hashtag generation, whereas BLIP gives higher lexical overlap and lower generalization. The retrieval-augmented approach exhibits better factual grounding, less hallucination, and great potential for scalable deployment in various clothing domains. These results demonstrate the use of retrieval-augmented generation as an effective and interpretable paradigm for automated and visually grounded fashion content generation.

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Moazzam Umer Gondal, Hamad Ul Qudous, Daniya Siddiqui, Asma Ahmad Farhan. 2025-11-24. From Pixels to Posts: Retrieval-Augmented Fashion Captioning and Hashtag Generation. https://arxiv.org/abs/2511.19149

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