TripleNet : Exploiting Complementary Features and Pseudo-Labels for Semi-Supervised Salient Object Detection
Due to the limited output categories, semi-supervised salient object detection faces challenges in adapting conventional semi-supervised strategies. To address this limitation, we propose a multi-branch architecture that extracts complementary features from labeled data. Specifically, we introduce T...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 34(2025) vom: 10., Seite 5628-5641 |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2025
|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
Volltext |