detect an object in an environment based at least on first sensor data representative of an image generated at a first time using an image sensor of an ego-machine;

based at least on the detection of the object, determine a first probability distribution corresponding to a location of the object in three dimensional (3D) world space;

generate a set of particles at one or more first locations within the first probability distribution having one or more first confidence values indicative of whether the object exists at the one or more first locations;

generate, at a second time after the first time, the set of particles at one or more second locations based at least on the one or more first locations and motion of the ego-machine between the first time and the second time, the set of particles at the one or more second locations including one or more second confidence values indicative of whether the object exists at the one or more second locations;

correlate the first sensor data with second sensor data representative of one or more depth detections generated using a depth sensor of the ego-machine at a third time;

based at least on the correlation, update the one or more second confidence values of the set of particles to one or more third confidence values indicative of whether the object exists at the one or more second locations; and

filter out one or more of the set of particles having associated one or more third confidence values less than a threshold confidence value to determine a subset of the particles.