AI RESEARCH
Stage-Adaptive Reliability Modeling for Continuous Valence-Arousal Estimation
arXiv CS.AI
•
ArXi:2603.11468v1 Announce Type: cross Continuous valence-arousal estimation in real-world environments is challenging due to inconsistent modality reliability and interaction-dependent variability in audio-visual signals. Existing approaches primarily focus on modeling temporal dynamics, often overlooking the fact that modality reliability can vary substantially across interaction stages. To address this issue, we propose SAGE, a Stage-Adaptive reliability modeling framework that explicitly estimates and calibrates modality-wise confidence during multimodal integration.