Class Relevance Learning for Out-of-Distribution Detection
Image classification plays a pivotal role across diverse robotic applications, yet challenges persist when models are deployed in real-world scenarios. These models often fail to detect out-of-distribution (OOD) samples, classes not included in their training. This makes OOD detection a significant…