Methods and systems of sensor fusion in cooperative perception systems

A cooperative perception system comprising:

• a plurality of imaging sensors each of the imaging sensors connected to provide output images to one of one or more first machine learning (ML) systems, the one or more ML systems comprising a plurality of layers and trained to process the output images to yield hypotheses, each of the hypotheses comprising:
• one or more objects and, for each of the objects, values for each of a plurality of regressed parameters and variation data indicating uncertainty of the value for each of the plurality of regressed parameters;
• and
• one or more processors connected to:
• receive feature maps from intermediate layers of the ML systems, the feature maps comprising partially-processed image data of the plurality of imaging sensors;
• and
• fuse the feature maps to yield a fused feature map;
• and
• process the fused feature map to yield a refined hypothesis, the refined hypotheses comprising:
• one or more objects and, for each of the objects, values for each of a plurality of regressed parameters.