Before revision:  The loss is model-independent and can be applied to various SGG models without extra supervision. The proposed CogTree loss consistently boosts the performance of several state-of-the-art models on the Visual Genome benchmark.
After revision:  The loss is model-agnostic and consistently boosting the performance of several state-of-the-art models on the Visual Genome benchmark.