3 papers
cs.CV2025
ProSAM: Enhancing the Robustness of SAM-based Visual Reference Segmentation with Probabilistic Prompts
Xiaoqi Wang, Clint Sebastian, Wenbin He +1
The recent advancements in large foundation models have driven the success of open-set image segmentation, a task focused on segmenting objects beyond predefined categories. Among…
cs.CV2025
VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels
Xiwei Xuan, Xiaoqi Wang, Wenbin He +4
The advances in multi-modal foundation models (FMs) (e.g., CLIP and LLaVA) have facilitated the auto-labeling of large-scale datasets, enhancing model performance in challenging do…
cs.CV2024
USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation
Xiaoqi Wang, Wenbin He, Xiwei Xuan +8
The open-vocabulary image segmentation task involves partitioning images into semantically meaningful segments and classifying them with flexible text-defined categories. The recen…