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cs.CV2026
Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation
Marco Stefani, Edoardo Parpaiola, Matteo Bino +5
High-risk applications of deep learning require precise characterization of model decision-making. We conduct a systematic explainability evaluation across Convolutional Neural Net…
cs.CV2026
Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation
Simone Mosco, Daniel Fusaro, Alberto Pretto
Understanding the surrounding environment is fundamental in autonomous driving and robotic perception. Distinguishing between known classes and previously unseen objects is crucial…