TIB : Detecting Unknown Objects via Two-Stream Information Bottleneck
Detecting diverse objects, including ones never-seen-before during training, is critical for the safe application of object detectors. To this end, a task of unsupervised out-of-distribution object detection (OOD-OD) is proposed to detect unknown objects without the reliance on an auxiliary dataset....
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2023), 1 vom: 10. Jan., Seite 611-625 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Online verfügbar |
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