2021
Defending Multimodal Fusion Models Against Single-Source Adversaries
CVPR 2021poster
Beyond achieving high performance across many vision tasks, multimodal models are expected to be robust to single-source faults due to the availability of redundant information between modalities. In this paper, we investigate the robustness of multimodal neural networks against worst-case (i.e., ad…