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Scene Graph Generation
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A scene graph is a structured representation of an image, where nodes in a scene graph correspond to object bounding boxes with their object categories, and edges correspond to their pairwise relationships between objects. The task of Scene Graph Generation is to generate a visually-grounded scene graph that most accurately correlates with an image.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions
Open World Scene Graph Generation using Vision Language Models
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding
Hi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments
A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing Scene Graph Generation
LLM Meets Scene Graph: Can Large Language Models Understand and Generate Scene Graphs? A Benchmark and Empirical Study
From Data to Modeling: Fully Open-vocabulary Scene Graph Generation
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
ORQA: A Benchmark and Foundation Model for Holistic Operating Room Modeling
Relation-R1: Cognitive Chain-of-Thought Guided Reinforcement Learning for Unified Relational Comprehension
Robo-SGG: Exploiting Layout-Oriented Normalization and Restitution for Robust Scene Graph Generation
Generalized Visual Relation Detection with Diffusion Models
SAMJAM: Zero-Shot Video Scene Graph Generation for Egocentric Kitchen Videos
NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
A Causal Adjustment Module for Debiasing Scene Graph Generation
Neuro-Symbolic Scene Graph Conditioning for Synthetic Image Dataset Generation
Universal Scene Graph Generation
Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation
DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation
FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing
Weakly Supervised Video Scene Graph Generation via Natural Language Supervision
KnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph Generation
Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation
Relation-aware Hierarchical Prompt for Open-vocabulary Scene Graph Generation
RelationField: Relate Anything in Radiance Fields
RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning
SceneLLM: Implicit Language Reasoning in LLM for Dynamic Scene Graph Generation
Benchmarking Federated Learning for Semantic Datasets: Federated Scene Graph Generation
Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation
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