Byeongkeun Kang

Learning from multimodal pseudo-labels for robust open-vocabulary instance and panoptic segmentation

This work addresses the challenge of open-vocabulary instance segmentation (OVIS) and open-set panoptic segmentation (OSPS), which aim to recognize both predefined and unseen object categories without exhaustive human annotations. Existing methods often suffer from noisy pseudo-masks, limited visual-textual grounding,...