MRCL extends pairwise spatial contrastive pre-training to multi-hop paths in scene graphs, yielding NDCG@5 = 0.748 on GQA graph retrieval and gains on spatial recognition and QA tasks.
A new way to repre- sent the relative position between areal objects.IEEE Trans- actions on pattern analysis and machine intelligence, 21(7): 634–643, 2002
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Multi-hop Relational Contrastive Learning: Extending Spatial Contrastive Pre-training Beyond Pairwise Relations
MRCL extends pairwise spatial contrastive pre-training to multi-hop paths in scene graphs, yielding NDCG@5 = 0.748 on GQA graph retrieval and gains on spatial recognition and QA tasks.