Placing objects in context via inpainting for out-of-distribution segmentation
When deploying a semantic segmentation model into the real world, it will inevitably encounter semantic classes that were not seen during training. To ensure a safe deployment of such systems, it is crucial to accurately evaluate and improve their anomaly segmentation capabilities. However, acquirin...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Springer
2024
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