A Supplementary Material A.1 AMWC Heuristic

Whenever a merge operation is performed the corresponding edge is contracted and new edges can potentially be created (Lines 7-17). Afterwards, the clusters belonging to non-partitionable class (i.e stuff) are merged. Table 2 contains the hyperparameters used for fully differentiable training. We can see that optimizing PQ surrogate gives better performance and using separate losses decreases the performance especially on'thing' classes. Table 5 showing that all trials improve over the baseline by fully differentiable training.