Unsupervised Out-of-Distribution Object Detection via PCA-Driven Dynamic Prototype Enhancement
To promote the application of object detectors in real scenes, out-of-distribution object detection (OOD-OD) is proposed to distinguish whether detected objects belong to the ones that are unseen during training or not. One of the key challenges is that detectors lack unknown data for supervision, a...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 33(2024) vom: 02., Seite 2431-2446 |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2024
|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
Volltext |