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- FashionDPO:Fine-tune Fashion Outfit Generation Model using Direct Preference Optimization11
This framework aims to provide a general fine-tuning approach to fashion generative models, refining a pre-trained fashion outfit generation model using automatically generated feedback, without the need to design a task-specific reward function.
- Smart Fitting Room: A One-stop Framework for Matching-aware Virtual Try-On9
A Hybrid Matching-aware Virtual Try-On Framework (HMaVTON), which combines retrieval-based and generative methods to foster a more personalized virtual try-on experience and significantly enhances the practicality of virtual try-on.
- GenWardrobe: A Fully Generative System for Travel Fashion Wardrobe Construction2
GenWardrobe is introduced, a fully generative system for travel fashion wardrobe construction that significantly outperforms traditional systems in both personalization and visual appeal and is encapsulated into an interactive web application.
- InstantAS: Minimum Coverage Sampling for Arbitrary-Size Image Generation1
This paper presents the InstantAS method for arbitrary-size image generation, and proposes the dynamic semantic guided cross-attention method, allowing for the control of different regions using different semantics.
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- Dual-Diffusional Generative Fashion Recommendation–
DualFashion is proposed, a Dual-Diffusional Generative Fashion Recommendation Architecture that jointly models image and text modalities for personalized and explainable recommendation and introduces a text-augmented fine-tuning strategy that enhances generation diversity and enables effective cross-modal knowledge transfer without incurring heavy computational costs.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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