4 papers · 1 filter
Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation
Jungmin Ko, Jungwon Park, Jimyeong Kim +3
Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object or attribute remains a fund…
Selective Aggregation of Attention Maps Improves Diffusion-Based Visual Interpretation
Jungwon Park, Jungmin Ko, Dongnam Byun +1
Numerous studies on text-to-image (T2I) generative models have utilized cross-attention maps to boost application performance and interpret model behavior. However, the distinct ch…
Progressive Multimodal Search and Reasoning for Knowledge-Intensive Visual Question Answering
Changin Choi, Wonseok Lee, Jungmin Ko +1
Knowledge-intensive visual question answering (VQA) requires external knowledge beyond image content, demanding precise visual grounding and coherent integration of visual and text…
Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models
Jungwon Park, Jungmin Ko, Dongnam Byun +2
Recent text-to-image diffusion models leverage cross-attention layers, which have been effectively utilized to enhance a range of visual generative tasks. However, our understandin…