7. The method of claim 6 , wherein the confidence loss term for the particular set of assignments is further based on, for each candidate bounding box that is not assigned to any of the object locations by the particular set of assignments, how close the confidence score for the candidate bounding box is to a second target confidence score for candidate bounding boxes that are not assigned to object locations, wherein the second target confidence score is lower than the first target confidence score.
7. The method of claim 6 , wherein the confidence loss term for the particular set of assignments is further based on, for each candidate bounding box that is not assigned to any of the object locations by the particular set of assignments, how close the confidence score for the candidate bounding box is to a second target confidence score for candidate bounding boxes that are not assigned to object locations, wherein the second target confidence score is lower than the first target confidence score. 8. The method of claim 7 , wherein the confidence loss F con for the particular set of assignments x satisfies: F con ⁡ ( x , c ) = - ∑ i , j ⁢ x i ⁢ ⁢ j ⁢ log ⁡ ( c i ) - ∑ i ⁢ ( 1 - ∑ j ⁢ x i ⁢ ⁢ j ) ⁢ log ⁡ ( 1 - c i ) , where i ranges from 1 to a total number of candidate bounding boxes, j ranges from 1 to a total number of object locations, c i is a confidence score for an i-th candidate bounding box, and x ij equals one if l i is assigned to a j-th object location by the particular set of assignments x and zero if l i is not assigned to the j-th object location by the particular set of assignments x.