1 citations · 1 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
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…
Disentangling Likes and Dislikes in Personalized Generative Explainable Recommendation
Ryotaro Shimizu, Takashi Wada, Yu Wang +9
Recent research on explainable recommendation generally frames the task as a standard text generation problem, and evaluates models simply based on the textual similarity between t…
A Fashion Item Recommendation Model in Hyperbolic Space
Ryotaro Shimizu, Yu Wang, Masanari Kimura +4
In this work, we propose a fashion item recommendation model that incorporates hyperbolic geometry into user and item representations. Using hyperbolic space, our model aims to cap…