12 citations · 15 across the 14 of their papers we have counts for
8 papers · 1 filter
Diversifying Long Prompt Image Generation through Structured Prompt Embedding Space Sampling
Bo-Kai Ruan, Teng-Fang Hsiao, Ling Lo +2
Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insufficiently understood. In this paper,…
Ranking-based Preference Optimization for Diffusion Models from Implicit User Feedback
Yi-Lun Wu, Bo-Kai Ruan, Chiang Tseng +1
Direct preference optimization (DPO) methods have shown strong potential in aligning text-to-image diffusion models with human preferences by training on paired comparisons. These…
Color Me Correctly: Bridging Perceptual Color Spaces and Text Embeddings for Improved Diffusion Generation
Sung-Lin Tsai, Bo-Lun Huang, Yu Ting Shen +5
Accurate color alignment in text-to-image (T2I) generation is critical for applications such as fashion, product visualization, and interior design, yet current diffusion models st…
Adversarial Attacks on VQA-NLE: Exposing and Alleviating Inconsistencies in Visual Question Answering Explanations
Yahsin Yeh, Yilun Wu, Bokai Ruan +1
Natural language explanations in visual question answering (VQA-NLE) aim to make black-box models more transparent by elucidating their decision-making processes. However, we find…
Score Replacement with Bounded Deviation for Rare Prompt Generation
Bo-Kai Ruan, Zi-Xiang Ni, Bo-Lun Huang +2
Diffusion models achieve impressive performance in high-fidelity image generation but often struggle with rare concepts that appear infrequently in the training distribution. Prior…
Anomaly Detection for Hybrid Butterfly Subspecies via Probability Filtering
Bo-Kai Ruan, Yi-Zeng Fang, Hong-Han Shuai +1
Detecting butterfly hybrids requires knowledge of the parent subspecies, and the process can be tedious when encountering a new subspecies. This study focuses on a specific scenari…
MAD: Makeup All-in-One with Cross-Domain Diffusion Model
Bo-Kai Ruan, Hong-Han Shuai
Existing makeup techniques often require designing multiple models to handle different inputs and align features across domains for different makeup tasks, e.g., beauty filter, mak…
TF-TI2I: Training-Free Text-and-Image-to-Image Generation via Multi-Modal Implicit-Context Learning in Text-to-Image Models
Teng-Fang Hsiao, Bo-Kai Ruan, Yi-Lun Wu +2
Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially…