3 papers
cs.CV2025
MoEdit: On Learning Quantity Perception for Multi-object Image Editing
Yanfeng Li, Kahou Chan, Yue Sun +6
Multi-object images are prevalent in various real-world scenarios, including augmented reality, advertisement design, and medical imaging. Efficient and precise editing of these im…
cs.CV2024
Synergy-Guided Regional Supervision of Pseudo Labels for Semi-Supervised Medical Image Segmentation
Tao Wang, Xinlin Zhang, Yuanbin Chen +4
Semi-supervised learning has received considerable attention for its potential to leverage abundant unlabeled data to enhance model robustness. Pseudo labeling is a widely used str…
cs.CV2024
ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection
Tao Wang, Xinlin Zhang, Zhenxuan Zhang +7
In clinical medicine, precise image segmentation can provide substantial support to clinicians. However, obtaining high-quality segmentation typically demands extensive pixel-level…