PROBABILISTIC PREDICTION OF OCCLUDED PEDESTRIANS AND OTHER ANIMATE OBJECTS IN AUTOMOTIVE ENVIRONMENTS

The disclosed systems and techniques are directed to identifying and responding to presence of target objects in occluded areas of driving environments. The techniques include training, using perception data associated with a first driving scene, a first machine learning model (MLM) to determine a location, within the first driving scene, of a target object masked with a masking transformation. The techniques further include training, using an output of the first MLM for a training driving scene, a second MLM to generate a map of probabilities of one or more target objects to be in an occluded region of the training driving scene, the training driving scene comprising at least one of the first driving scene or a second driving scene, and causing the second MLM to be deployed on an autonomous vehicle.