Benchmarking the Robustness of Spatial-Temporal Models Against Corruptions

Chenyu Yi, Siyuan Yang, Haoliang Li +2

The state-of-the-art deep neural networks are vulnerable to common corruptions (e.g., input data degradations, distortions, and disturbances caused by weather changes, system error…