Yuanya Zhuo

ReDA: discrepancy guided multimodal fusion for audio-visual deception detection

The key to the approach is a discrepancy-aware dynamic fusion module, which treats cross-modality inconsistency as an explicit indicator of deception, and creates an interaction representation from which a sample-specific reliability level of each modality can be inferred and dynamically adjusted.