Papers Scene Graph Generation
“Scene Graph Generation” 태그가 달린 논문 365편 · 필터 해제
CAGE-SGG: Counterfactual Active Graph Evidence for Open-Vocabulary Scene Graph Generation
Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible and fine-grained relation phrases beyond a fixed predicate vocabulary. While recent vision-language models greatly expand the sema…
Scene Graph GenerationReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation
Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible relation phrases beyond a fixed predicate set. Existing methods usually treat annotated triplets as positives and all unannotated …
Scene Graph GenerationGraph LearningMOSA: Motion-Guided Semantic Alignment for Dynamic Scene Graph Generation
Dynamic Scene Graph Generation (DSGG) aims to structurally model objects and their dynamic interactions in video sequences for high-level semantic understanding. However, existing methods struggle with fine-grained relat…
Scene Graph GenerationCan We Build Scene Graphs, Not Classify Them? FlowSG: Progressive Image-Conditioned Scene Graph Generation with Flow Matching
Scene Graph Generation (SGG) unifies object localization and visual relationship reasoning by predicting boxes and subject-predicate-object triples. Yet most pipelines treat SGG as a one-shot, deterministic classificatio…
Scene Graph GenerationObject LocalizationSenBen: Sensitive Scene Graphs for Explainable Content Moderation
Content moderation systems classify images as safe or unsafe but lack spatial grounding and interpretability: they cannot explain what sensitive behavior was detected, who is involved, or where it occurs. We introduce th…
Scene Graph GenerationObject DetectionToLL: Topological Layout Learning with Asymmetric Cross-View Structural Distillation for 3D Scene Graph Generation Pretraining
3D Scene Graph (3DSG) generation plays a pivotal role in spatial understanding and affordance perception. To mitigate generalization issues from data scarcity, joint-embedding and generative proxy tasks are proposed to p…
Representation LearningScene Graph GenerationModernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation
Semantic world models enable embodied agents to reason about objects, relations, and spatial context beyond purely geometric representations. In Organic Computing, such models are a key enabler for objective-driven self-…
Reinforcement LearningScene Graph GenerationReLaGS: Relational Language Gaussian Splatting
Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-centric or rely on costly training for int…
Scene Graph GenerationRelational ReasoningGraph Neural NetworkTowards Spatio-Temporal World Scene Graph Generation from Monocular Videos
Spatio-temporal scene graphs provide a principled representation for modeling evolving object interactions, yet existing methods remain fundamentally frame-centric: they reason only about currently visible objects, disca…
Scene Graph GenerationScene Understanding3D ReconstructionREACT++: Efficient Cross-Attention for Real-Time Scene Graph Generation
Scene Graph Generation (SGG) is a task that encodes visual relationships between objects in images as graph structures. SGG shows significant promise as a foundational component for downstream tasks, such as reasoning fo…
Scene Graph GenerationObject DetectionSGR3 Model: Scene Graph Retrieval-Reasoning Model in 3D
3D scene graphs provide a structured representation of object entities and their relationships, enabling high-level interpretation and reasoning for robots while remaining intuitively understandable to humans. Existing a…
Scene Graph GenerationRelational Reasoning3D ReconstructionHazard-Aware Traffic Scene Graph Generation
Maintaining situational awareness in complex driving scenarios is challenging. It requires continuously prioritizing attention among extensive scene entities and understanding how prominent hazards might affect the ego v…
Scene Graph GenerationScene UnderstandingSSR: Pushing the Limit of Spatial Intelligence with Structured Scene Reasoning
While Multimodal Large Language Models (MLLMs) excel in semantic tasks, they frequently lack the "spatial sense" essential for sophisticated geometric reasoning. Current models typically suffer from exorbitant modality-a…
Scene Graph GenerationSpatial ReasoningMA3DSG: Multi-Agent 3D Scene Graph Generation for Large-Scale Indoor Environments
Current 3D scene graph generation (3DSGG) approaches heavily rely on a single-agent assumption and small-scale environments, exhibiting limited scalability to real-world scenarios. In this work, we introduce Multi-Agent …
Scene Graph GenerationVIZOR: Viewpoint-Invariant Zero-Shot Scene Graph Generation for 3D Scene Reasoning
Scene understanding and reasoning has been a fundamental problem in 3D computer vision, requiring models to identify objects, their properties, and spatial or comparative relationships among the objects. Existing approac…
Scene Graph GenerationScene UnderstandingVOST-SGG: VLM-Aided One-Stage Spatio-Temporal Scene Graph Generation
Spatio-temporal scene graph generation (ST-SGG) aims to model objects and their evolving relationships across video frames, enabling interpretable representations for downstream reasoning tasks such as video captioning a…
Visual Question AnsweringScene Graph GenerationCommon Sense ReasoningVideo CaptioningRS-Net: Context-Aware Relation Scoring for Dynamic Scene Graph Generation
Dynamic Scene Graph Generation (DSGG) models how object relations evolve over time in videos. However, existing methods are trained only on annotated object pairs and lack guidance for non-related pairs, making it diffic…
Scene Graph GenerationSpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards
Multimodal large language models (MLLMs) have achieved remarkable progress in vision-language tasks, but continue to struggle with spatial reasoning. Existing spatial MLLMs rely on large-scale datasets, explicit 3D input…
Scene Graph GenerationReinforcement LearningSpatial ReasoningVisual ReasoningOpen-World 3D Scene Graph Generation for Retrieval-Augmented Reasoning
Understanding 3D scenes in open-world settings poses fundamental challenges for vision and robotics, particularly due to the limitations of closed-vocabulary supervision and static annotations. To address this, we propos…
Scene Graph GenerationScene UnderstandingQuestion AnsweringVisual GroundingInteraction-Centric Knowledge Infusion and Transfer for Open-Vocabulary Scene Graph Generation
Open-vocabulary scene graph generation (OVSGG) extends traditional SGG by recognizing novel objects and relationships beyond predefined categories, leveraging the knowledge from pre-trained large-scale models. Existing O…
Scene Graph GenerationKnowledge DistillationGeneral Knowledge