Before revision:  In this paper, we propose sensor-aware multi-modal fusion strategiesfor 2D object detection in harsh lighting conditions. Our network learns to estimate the measurement reliability of each sensor modality in the form of scalar weightsand masks, without prior knowledge of the sensor characteristics. The obtained weights are assigned to the extracted feature maps which are subsequently fused and passed to the transformer encoder-decoder network for object detection . This is critical in the case of asymmetric sensor failures and to prevent any severe consequences .
After revision:  In this paper, we propose sensor-aware multi-modal fusion strategiesfor 2D object detector, and propose deterministic and stochastic sensor-aware feature fusion strategies .