3 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.AI2026
Learning to Recover Task Experts from a Multi-Task Merged Model
Jinwook Jung, Taegyu Kim, Kumju Jo +1
Multi-task model merging aims to consolidate several task-specific experts into a unified model, yet static merging consistently suffers from parameter interference. While dynamic…
cs.CV2025
SeeDiff: Off-the-Shelf Seeded Mask Generation from Diffusion Models
Joon Hyun Park, Kumju Jo, Sungyong Baik
Entrusted with the goal of pixel-level object classification, the semantic segmentation networks entail the laborious preparation of pixel-level annotation masks. To obtain pixel-l…