2 papers
cs.CV2026
Text-to-seed generation: Training-free open-vocabulary seeded semantic segmentation via re-purposing diffusion as text-guided seed generator
Kumju Jo, Heesun Jung, Sungyong Baik
Open-vocabulary semantic segmentation (OVSS) aims to segment image regions corresponding to arbitrary text queries. Although the Segment Anything Model (SAM) is a powerful foundati…
cs.CV2026
Decoupled Guidance: Disentangling Subject and Context Pathways in Text-to-Image Personalization
Seongmin Kim, Kyucheol Shin, Heesun Jung +2
Text-to-image personalization aims to generate a user-provided subject in novel scenes described by text. However, most existing methods encode subject identity (fidelity) and cont…