Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation 事件

Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation arXiv:2606.06369v1 Announce Type: new Abstract: Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture reliable visual commonsense knowledge. We propose a model-agnostic, semantically-guided knowledge refinement framework that systematically mines commonsense-grounded constraints from training data - capturing spatial, functio