Learning a Semantic Calibration Network for Open-Vocabulary Semantic Segmentation
Semantic image segmentation assigns a predefined category label to each pixel, has achieved significant progress lately. Open-Vocabulary Segmentation (OVS) extends the segmentation task from a fixed set to an open set, enabling the identification and segmentation of novel concepts based on arbitrary text inputs, such as category names or descriptions. In this paper, we propose a novel Semantic Calibration Network (SCN) for open-vocabulary semantic segmentation. Different from prior approaches that focus on feature aggregation or simple fine-tuning of pre-trained models, SCN refines the mask classification process by explicitly modeling the semantic correlations between classes, aiming to ...
| Authors | Yang Sun, Tao Wang, Anastasia Ioannou et al. |
|---|---|
| Primary category | cs.CV |
| Published | 6 June 2026 |
| Last updated at source | 6 June 2026 |
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