Papers Scene Graph Generation
“Scene Graph Generation” 태그가 달린 논문 365편 · 필터 해제
Case Study: Transformer-Based Solution for the Automatic Digitization of Gas Plants
The energy transition is a key theme of the last decades to determine a future of eco-sustainability, and an area of such importance cannot disregard digitization, innovation and the new technological tools available. Th…
Scene Graph GenerationRelational ReasoningObject DetectionZING-3D: Zero-shot Incremental 3D Scene Graphs via Vision-Language Models
Understanding and reasoning about complex 3D environments requires structured scene representations that capture not only objects but also their semantic and spatial relationships. While recent works on 3D scene graph ge…
Scene Graph GenerationESCA: Contextualizing Embodied Agents via Scene-Graph Generation
Multi-modal large language models (MLLMs) are making rapid progress toward general-purpose embodied agents. However, existing MLLMs do not reliably capture fine-grained links between low-level visual features and high-le…
Scene Graph GenerationMeasuring Image-Relation Alignment: Reference-Free Evaluation of VLMs and Synthetic Pre-training for Open-Vocabulary Scene Graph Generation
Scene Graph Generation (SGG) encodes visual relationships between objects in images as graph structures. Thanks to the advances of Vision-Language Models (VLMs), the task of Open-Vocabulary SGG has been recently proposed…
Scene Graph GenerationTRKT: Weakly Supervised Dynamic Scene Graph Generation with Temporal-enhanced Relation-aware Knowledge Transferring
Dynamic Scene Graph Generation (DSGG) aims to create a scene graph for each video frame by detecting objects and predicting their relationships. Weakly Supervised DSGG (WS-DSGG) reduces annotation workload by using an un…
Scene Graph GenerationObject LocalizationStatistical Confidence Rescoring for Robust 3D Scene Graph Generation from Multi-View Images
Modern 3D semantic scene graph estimation methods utilize ground truth 3D annotations to accurately predict target objects, predicates, and relationships. In the absence of given 3D ground truth representations, we explo…
Scene Graph GenerationFROSS: Faster-than-Real-Time Online 3D Semantic Scene Graph Generation from RGB-D Images
The ability to abstract complex 3D environments into simplified and structured representations is crucial across various domains. 3D semantic scene graphs (SSGs) achieve this by representing objects as nodes and their in…
Scene Graph GenerationScene UnderstandingSPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning
Panoptic Scene Graph Generation (PSG) integrates instance segmentation with relation understanding to capture pixel-level structural relationships in complex scenes. Although recent approaches leveraging pre-trained visi…
DenoisingGraph GenerationInstance SegmentationPanoptic Scene Graph Generation+4CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations
2D scene graphs provide a structural and explainable framework for scene understanding. However, current work still struggles with the lack of accurate scene graph data. To overcome this data bottleneck, we present CoPa-…
Graph GenerationRelationScene Graph GenerationScene UnderstandingCAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery
Understanding the intricate workflows of cataract surgery requires modeling complex interactions between surgical tools, anatomical structures, and procedural techniques. Existing datasets primarily address isolated aspe…
Graph GenerationScene Graph GenerationHOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions
When humans and robotic agents coexist in an environment, scene understanding becomes crucial for the agents to carry out various downstream tasks like navigation and planning. Hence, an agent must be capable of localizi…
Graph GenerationHuman-Object Interaction DetectionScene Graph GenerationScene UnderstandingOpen World Scene Graph Generation using Vision Language Models
Scene-Graph Generation (SGG) seeks to recognize objects in an image and distill their salient pairwise relationships. Most methods depend on dataset-specific supervision to learn the variety of interactions, restricting …
Graph GenerationScene Graph GenerationEgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding
Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-paced, occlusion-heavy environment, necessitating advanced perception models to enhance safety and efficiency. Existing da…
Action RecognitionGraph GenerationScene Graph GenerationHi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments
Autonomous operation of service robotics in human-centric scenes remains challenging due to the need for understanding of changing environments and context-aware decision-making. While existing approaches like topologica…
Graph GenerationHuman-Object Interaction DetectionNeRFScene Graph Generation+1A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing Scene Graph Generation
Existing two-stage Scene Graph Generation (SGG) frameworks typically incorporate a detector to extract relationship features and a classifier to categorize these relationships; therefore, the training paradigm follows a …
Graph GenerationScene Graph GenerationFrom Data to Modeling: Fully Open-vocabulary Scene Graph Generation
We present OvSGTR, a novel transformer-based framework for fully open-vocabulary scene graph generation that overcomes the limitations of traditional closed-set models. Conventional methods restrict both object and relat…
Graph GenerationKnowledge DistillationNovel ConceptsOpen-vocabulary object detection+3LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical Study
The remarkable reasoning and generalization capabilities of Large Language Models (LLMs) have paved the way for their expanding applications in embodied AI, robotics, and other real-world tasks. To effectively support th…
Graph GenerationScene Graph GenerationSCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
Despite the dominance of convolutional and transformer-based architectures in image-to-image retrieval, these models are prone to biases arising from low-level visual features, such as color. Recognizing the lack of sema…
counterfactualGraph GenerationGraph SimilarityImage Captioning+3ORQA: A Benchmark and Foundation Model for Holistic Operating Room Modeling
The real-world complexity of surgeries necessitates surgeons to have deep and holistic comprehension to ensure precision, safety, and effective interventions. Computational systems are required to have a similar level of…
Graph GenerationKnowledge DistillationLanguage ModelingLanguage Modelling+5Relation-R1: Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relational Comprehension
Recent advances in multi-modal large language models (MLLMs) have significantly improved object-level grounding and region captioning, but remain limited in visual relation understanding (\eg, scene graph generation), pa…
Graph GenerationReinforcement Learning (RL)RelationScene Graph Generation