Distribution of Mentioned IDs17R2>= 3# of IDs

For each image's list of candidate objects, we heuristically downsample to a set of "most interesting" regions by: 1) selecting the at-most k " 4 largest/most central people; 2) keeping the most central/large objects; 3) over-sampling rarer objects according to prior frequency of detection in the LVIS vocabulary; 4) limiting the number of objects of a single type per-image; and 5) downsampling overlapping region proposals to encourage broader coverage of the pixel area of the image.