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Human-Inspired Scene Understanding: A Grounded Cognition Method for Unbiased Scene Graph Generation
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Summary
Researchers propose the Grounded Cognition Method (GCM) for unbiased scene graph generation, aiming to fix the long-tailed bias that makes existing scene graph generation methods favor frequent predicates over semantically accurate ones. GCM models simulation, bodily states and situated action, using an Out Domain Knowledge Injection module, a Semantic Group Aware Synthesizer, and a Shapley Enhanced Multimodal Counterfactual module. Experiments on Visual Genome, GQA and Open Images V6 reportedly show GCM outperforming state-of-the-art methods and achieving a better trade-off.