Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention
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Abstract (arXiv)
Scene Graph Generation (SGG) offers a structured representation critical in many computer vision applications. Traditional SGG approaches, however, are limited by a closed-set assumption, restricting their ability to recognize only predefined object and relation categories. To overcome this, we categorize SGG scenarios into four distinct settings based on the node and edge: Closed-set SGG, Open Vocabulary (object) Detection-based SGG (OvD-SGG), Open Vocabulary Relation-based SGG (OvR-SGG), and Open Vocabulary Detection + Relationbased SGG (OvD+R-SGG). While object-centric open vocabulary SGG has been studied recently, the more challenging problem of relation-involved open-vocabulary SGG remains relatively unexplored. To fill this gap, we propose a unified framework named OvSGTR towards fully open vocabulary SGG from a holistic view. The proposed framework is an end-to-end transformer architecture, which learns a visual-concept alignment for both nodes and edges, enabling the model to recognize unseen categories. For the more challenging settings of relation-involved open vocabulary SGG, the proposed approach integrates relation-aware pretraining utilizing image-caption data and retains visual-concept alignment through knowledge distillation. Comprehensive experimental results on the Visual Genome benchmark demonstrate the effectiveness and superiority of the proposed framework. Our code is available at https://github.com/gpt4vision/OvSGTR/.
Key facts. Cited by 29 papers in the map (data through 14 Oct 2026). Builds on 43 of its 53 references that are in the map. First posted on arXiv 18 Nov 2023.
Builds on
43 of 53 references.
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Citing papers per year: 2023: 1; 2024: 5; 2025: 12; 2026: 11.
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- 2025Open World Scene Graph Generation using Vision Language Modelscited by 7
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- 2024Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipationcited by 6
- 2024What Makes a Scene ? Scene Graph-based Evaluation and Feedback for Controllable Generationcited by 6
- 2025Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scenecited by 6
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12 most cited of 22 All 22 (JSON)
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- 2026SceneGraphGrounder: Zero-Shot 3D Visual Grounding via Structured Scene Graph Matching20 May 2026
- 2026ReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation24 Apr 2026
- 2026CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation24 Apr 2026
- 2026Caption Generation for Dongba Paintings via Prompt Learning and Semantic Fusion24 Mar 2026
- 2026SR-Nav: Spatial Relationships Matter for Zero-shot Object Goal Navigation19 Mar 2026
- 2026SGG-Rrm 3: From Next-Token Prediction to End-to-End Unbiased Scene Graph Generation9 Mar 2026
- 2026Graph is a Substrate Across Data Modalities29 Jan 2026
- 2026The Semantic Lifecycle in Embodied AI: Acquisition, Representation and Storage via Foundation Models12 Jan 2026
- 2025Object-Centric Framework for Video Moment Retrieval20 Dec 2025
- 2025Interaction-Centric Knowledge Infusion and Transfer for Open-Vocabulary Scene Graph Generation8 Nov 2025
12 newest of 22 All 22 (JSON)
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