Papers Scene Graph Generation
“Scene Graph Generation” 태그가 달린 논문 365편 · 필터 해제
Robo-SGG: Exploiting Layout-Oriented Normalization and Restitution for Robust Scene Graph Generation
In this paper, we introduce a novel method named Robo-SGG, i.e., Layout-Oriented Normalization and Restitution for Robust Scene Graph Generation. Compared to the existing SGG setting, the robust scene graph generation ai…
Graph GenerationScene Graph GenerationGeneralized Visual Relation Detection with Diffusion Models
Visual relation detection (VRD) aims to identify relationships (or interactions) between object pairs in an image. Although recent VRD models have achieved impressive performance, they are all restricted to pre-defined r…
Graph GenerationHuman-Object Interaction DetectionImage CaptioningImage Retrieval+3SAMJAM: Zero-Shot Video Scene Graph Generation for Egocentric Kitchen Videos
Video Scene Graph Generation (VidSGG) is an important topic in understanding dynamic kitchen environments. Current models for VidSGG require extensive training to produce scene graphs. Recently, Vision Language Models (V…
Graph GenerationObjectScene Graph GenerationVideo scene graph generationNuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
Recent advancements in Vision-Language Models (VLMs) have demonstrated strong potential for autonomous driving tasks. However, their spatial understanding and reasoning-key capabilities for autonomous driving-still exhib…
3d scene graph generationAutonomous DrivingGraph GenerationScene Graph Generation+1A Causal Adjustment Module for Debiasing Scene Graph Generation
While recent debiasing methods for Scene Graph Generation (SGG) have shown impressive performance, these efforts often attribute model bias solely to the long-tail distribution of relationships, overlooking the more prof…
AttributeCausal InferenceGraph GenerationScene Graph GenerationNeuro-Symbolic Scene Graph Conditioning for Synthetic Image Dataset Generation
As machine learning models increase in scale and complexity, obtaining sufficient training data has become a critical bottleneck due to acquisition costs, privacy constraints, and data scarcity in specialised domains. Wh…
Dataset GenerationGraph GenerationScene Graph GenerationSynthetic Data Generation+1What can Off-the-Shelves Large Multi-Modal Models do for Dynamic Scene Graph Generation?
Dynamic Scene Graph Generation (DSGG) for videos is a challenging task in computer vision. While existing approaches often focus on sophisticated architectural design and solely use recall during evaluation, we take a cl…
DecoderGraph GenerationScene Graph GenerationTriplet+1Universal Scene Graph Generation
Scene graph (SG) representations can neatly and efficiently describe scene semantics, which has driven sustained intensive research in SG generation. In the real world, multiple modalities often coexist, with different t…
Graph GenerationScene Graph GenerationConformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation
Scene Graph Generation (SGG) aims to represent visual scenes by identifying objects and their pairwise relationships, providing a structured understanding of image content. However, inherent challenges like long-tailed c…
Conformal PredictionGraph GenerationPredictionScene Graph Generation+1DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation
Top-leading solutions for Video Scene Graph Generation (VSGG) typically adopt an offline pipeline. Though demonstrating promising performance, they remain unable to handle real-time video streams and consume large GPU me…
DenoisingGPUGraph GenerationScene Graph Generation+1FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction
The concept of 3D scene graphs is increasingly recognized as a powerful semantic and hierarchical representation of the environment. Current approaches often address this at a coarse, object-level resolution. In contrast…
3d scene graph generationGraph GenerationScene Graph GenerationMM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipment for enhancing surgical assistance, situational awareness, and patient …
2D Panoptic SegmentationGraph GenerationLanguage ModelingLanguage Modelling+2Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing
Video Scene Graph Generation (VidSGG) aims to capture dynamic relationships among entities by sequentially analyzing video frames and integrating visual and semantic information. However, VidSGG is challenged by signific…
Graph GenerationScene Graph GenerationTripletVideo scene graph generationKnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph Generation
A scene graph is a key image representation in visual reasoning. The generalisability of Scene Graph Generation (SGG) methods is crucial for reliable reasoning and real-world applicability. However, imbalanced training d…
Common Sense ReasoningGraph Generationobject-detectionObject Detection+4Weakly Supervised Video Scene Graph Generation via Natural Language Supervision
Existing Video Scene Graph Generation (VidSGG) studies are trained in a fully supervised manner, which requires all frames in a video to be annotated, thereby incurring high annotation cost compared to Image Scene Graph …
Graph GenerationImage CaptioningLarge Language ModelScene Graph Generation+1Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation
High-Definition (HD) maps play a crucial role in autonomous vehicle navigation, complementing onboard perception sensors for improved accuracy and safety. Traditional HD map generation relies on dedicated mapping vehicle…
Graph GenerationScene Graph GenerationUniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation
Scene Graph Generation(SGG) is a scene understanding task that aims at identifying object entities and reasoning their relationships within a given image. In contrast to prevailing two-stage methods based on a large obje…
DecoderGraph GenerationObjectScene Graph Generation+2Navigating the Unseen: Zero-shot Scene Graph Generation via Capsule-Based Equivariant Features
In scene graph generation (SGG), the accurate prediction of unseen triples is essential for its effectiveness in downstream vision-language tasks. We hypothesize that the predicates of unseen triples can be viewed as…
AttributeGraph GenerationScene Graph GenerationZero-Shot Scene Graph GenerationHybrid Reciprocal Transformer with Triplet Feature Alignment for Scene Graph Generation
Scene graph generation is a pivotal task in computer vision, focusing on comprehensive identification of visual relation tuples embedded within images. The advancement of methods involving triplets has sought to enha…
Graph GenerationRelationScene Graph GenerationTripletLearning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene
The latest emerged 4D Panoptic Scene Graph (4D-PSG) provides an advanced-ever representation for comprehensively modeling the dynamic 4D visual real world. Unfortunately, current pioneering 4D-PSG research can largel…
Graph GenerationLarge Language ModelPanoptic Scene Graph GenerationScene Graph Generation+1