A dual-query scene graph generation method unifies detector-based and query-based reasoning in a single decoder, achieving state-of-the-art results on Visual Genome, Open Images v6, and GQA-200.
In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2representative citing papers
DeWorldSG improves 3D scene graph generation from RGB-D sequences by using depth-guided 3D Gaussian object nodes and V-JEPA 2 world-model priors for spatiotemporal relation refinement, reporting large recall gains on 3DSSG and ReplicaSSG.
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Revisiting Scene Graph Generation from the Perspective of Detector-Conditioned Reachability
A dual-query scene graph generation method unifies detector-based and query-based reasoning in a single decoder, achieving state-of-the-art results on Visual Genome, Open Images v6, and GQA-200.
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DeWorldSG: Depth-Aware 3D Semantic Scene Graph Generation via World-Model Priors
DeWorldSG improves 3D scene graph generation from RGB-D sequences by using depth-guided 3D Gaussian object nodes and V-JEPA 2 world-model priors for spatiotemporal relation refinement, reporting large recall gains on 3DSSG and ReplicaSSG.