Toward a Realistic Benchmark for Out-of-Distribution Detection

Pietro Recalcati, Fabio Garcea, Luca Piano +2

Deep neural networks are increasingly used in a wide range of technologies and services, but remain highly susceptible to out-of-distribution (OOD) samples, that is, drawn from a d…