Context-aware Bayesian Fusion for Multimodal Object Detection
This work proposes a novel context-aware multimodal late fusion approach that integrates a lightweight gating network within the probabilistic calibration framework and dynamically modulates the detection outputs of pre-trained object detectors based on the inferred context, without retraining of the detectors.