Multimodal graph inference network for scene graph generation
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02304-7
Abstract: A scene graph can describe images concisely and structurally. However, existing methods of scene graph generation have low capabilities of inferring certain relationships, because of the lack of semantic information and their heavy dependence on… read more here.
Keywords: inference; graph generation; scene graph; graph ... See more keywords
Scene Graph Generation Using Depth, Spatial, and Visual Cues in 2D Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2021.3139000
Abstract: To understand an image or a scene properly, it is necessary to identify objects participating in the scene, their relationships, and various attributes that describe their properties. A scene graph is a high-level representation that… read more here.
Keywords: scene graph; depth spatial; graph generation; using depth ... See more keywords
Towards Open-Set Scene Graph Generation with Unknown Objects
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3145465
Abstract: Scene graph generation (SGG) aims to detect objects and their relationships in an image, thereby enabling a detailed understanding of a complex scene for various real-world applications. In SGG applications such as robot vision, it… read more here.
Keywords: scene graph; graph generation; unknown objects; open set ... See more keywords
Relationship-Aware Unknown Object Detection for Open-Set Scene Graph Generation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3450908
Abstract: Scene graph generation (SGG) aims to detect the relationships of objects in an image. Recently, it has been extended to open-set SGG, which also considers unknown objects unseen in a training phase and thereby enables… read more here.
Keywords: scene graph; detection; set sgg; sgg ... See more keywords
Alert-Driven Attack Graph Generation Using S-PDFA
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2021.3117348
Abstract: Ideal cyber threat intelligence (CTI) includes insights into attacker strategies that are specific to a network under observation. Such CTI currently requires extensive expert input for obtaining, assessing, and correlating system vulnerabilities into a graphical… read more here.
Keywords: attack graph; graph generation; generation using; driven attack ... See more keywords
Hierarchical Prototype Learning via Aggregation-Decomposition for Fine-Grained Geospatial Scene Graph Generation
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2025.3629400
Abstract: Geospatial scene graph generation (G-SGG) in remote sensing imagery (RSI) aims to identify triplets that reflect interactions among objects on the Earth’s surface. A key challenge in G-SGG is the large intraclass variation of geospatial… read more here.
Keywords: scene graph; prototype learning; prototype; hierarchical prototype ... See more keywords
State-Aware Compositional Learning Toward Unbiased Training for Scene Graph Generation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3224872
Abstract: How to avoid biased predictions is an important and active research question in scene graph generation (SGG). Current state-of-the-art methods employ debiasing techniques such as resampling and causality analysis. However, the role of intrinsic cues… read more here.
Keywords: scene graph; graph generation; state; compositional learning ... See more keywords
Adaptive Feature Learning for Unbiased Scene Graph Generation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2024.3374644
Abstract: Scene Graph Generation (SGG) aims to detect all objects and identify their pairwise relationships in the scene. Recently, tremendous progress has been made in exploring better context relationship representations. Previous work mainly focuses on contextual… read more here.
Keywords: scene graph; feature; feature learning; graph generation ... See more keywords
Graphusion: Latent Diffusion for Graph Generation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2024.3389783
Abstract: Graph generation is a fundamental task in machine learning with broad impacts on numerous real-world applications such as biomedical discovery and social science. Most recently, generative models, especially diffusion models (DMs), have shown great promise… read more here.
Keywords: graphusion; diffusion; space; graph ... See more keywords
Toward Region-Aware Attention Learning for Scene Graph Generation.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3086066
Abstract: Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues.… read more here.
Keywords: graph generation; region; attention; scene graph ... See more keywords
Debiased Scene Graph Generation for Dual Imbalance Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3198965
Abstract: Scene graph generation (SGG) is one of the hottest topics in computer vision and has attracted many interests since it provides rich semantic information between objects. In practice, the SGG datasets are often dual imbalanced,… read more here.
Keywords: scene graph; graph; graph generation; imbalance ... See more keywords