Papers Scene Graph Detection
“Scene Graph Detection” 태그가 달린 논문 11편 · 필터 해제
DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation
Scene graph generation aims to capture detailed spatial and semantic relationships between objects in an image, which is challenging due to incomplete labelling, long-tailed relationship categories, and relational semant…
Graph GenerationGraph MatchingPanoptic Scene Graph GenerationRelation+2Joint Generative Modeling of Scene Graphs and Images via Diffusion Models
In this paper, we present a novel generative task: joint scene graph - image generation. While previous works have explored image generation conditioned on scene graphs or layouts, our task is distinctive and important a…
Graph GenerationImage GenerationScene Graph DetectionScene Graph GenerationEnhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge
This work introduces an enhanced approach to generating scene graphs by incorporating both a relationship hierarchy and commonsense knowledge. Specifically, we begin by proposing a hierarchical relation head that exploit…
Large Language ModelMultimodal Deep LearningPredicate ClassificationRelation+4NeuSyRE: Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph Enrichment
Neuro-symbolic hybrid approaches are inevitable for seamless high-level understanding and reasoning about visual scenes. Scene Graph Generation (SGG) is a symbolic image representation approach based on deep neural netwo…
Caption GenerationCommon Sense ReasoningGraph GenerationImage Captioning+7Open-Vocabulary Object Detection via Scene Graph Discovery
In recent years, open-vocabulary (OV) object detection has attracted increasing research attention. Unlike traditional detection, which only recognizes fixed-category objects, OV detection aims to detect objects in an op…
DecoderGraph GenerationObjectobject-detection+6Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and Reasoning
Scene graph generation aims to capture the semantic elements in images by modelling objects and their relationships in a structured manner, which are essential for visual understanding and reasoning tasks including image…
Common Sense ReasoningGraph GenerationImage CaptioningImage Generation+9Fine-Grained Scene Graph Generation with Data Transfer
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images. Recent works have made a steady progress on SGG, and provide useful tools for high-level vision and language understand…
Graph GenerationPredicate ClassificationScene Graph ClassificationScene Graph Detection+2Relation Regularized Scene Graph Generation
Scene graph generation (SGG) is built on top of detected objects to predict object pairwise visual relations for describing the image content abstraction. Existing works have revealed that if the links between objects ar…
Graph ClassificationGraph GenerationObjectPredicate Classification+4Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
Dynamic scene graph generation from a video is challenging due to the temporal dynamics of the scene and the inherent temporal fluctuations of predictions. We hypothesize that capturing long-term temporal dependencies is…
Graph GenerationObjectScene Graph DetectionScene Graph Generation+1Recovering the Unbiased Scene Graphs from the Biased Ones
Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects. Recently, more efforts have been paid to the long tail prob…
Missing LabelsScene Graph ClassificationScene Graph DetectionScene Graph Generation+3Energy-Based Learning for Scene Graph Generation
Traditional scene graph generation methods are trained using cross-entropy losses that treat objects and relationships as independent entities. Such a formulation, however, ignores the structure in the output space, in a…
Graph GenerationInductive BiasScene Graph ClassificationScene Graph Detection+2