1 citations · 1 across the 3 of their papers we have counts for
7 papers
Reference-Free Image Quality Assessment for Virtual Try-On via Human Feedback
Yuki Hirakawa, Takashi Wada, Ryotaro Shimizu +6
As virtual try-on (VTON) systems become increasingly important in fashion e-commerce, there is a growing need for reliable reference-free evaluation methods, since ground-truth ima…
MultiEmo-Bench: Multi-label Visual Emotion Analysis for Multi-modal Large Language Models
Tianwei Chen, Takuya Furusawa, Yuki Hirakawa +3
This paper introduces a multi-label visual emotion analysis benchmark dataset for comprehensively evaluating the ability of multimodal large language models (MLLMs) to predict the…
Masked Language Prompting for Generative Data Augmentation in Few-shot Fashion Style Recognition
Yuki Hirakawa, Ryotaro Shimizu
Constructing dataset for fashion style recognition is challenging due to the inherent subjectivity and ambiguity of style concepts. Recent advances in text-to-image models have fac…
Static Word Embeddings for Sentence Semantic Representation
Takashi Wada, Yuki Hirakawa, Ryotaro Shimizu +2
We propose new static word embeddings optimised for sentence semantic representation. We first extract word embeddings from a pre-trained Sentence Transformer, and improve them wit…
Fashionability-Enhancing Outfit Image Editing with Conditional Diffusion Models
Qice Qin, Yuki Hirakawa, Ryotaro Shimizu +2
Image generation in the fashion domain has predominantly focused on preserving body characteristics or following input prompts, but little attention has been paid to improving the…
An Empirical Analysis of GPT-4V's Performance on Fashion Aesthetic Evaluation
Yuki Hirakawa, Takashi Wada, Kazuya Morishita +4
Fashion aesthetic evaluation is the task of estimating how well the outfits worn by individuals in images suit them. In this work, we examine the zero-shot performance of GPT-4V on…