Results 241 to 250 of about 90,374 (275)

VIZOR: Viewpoint-Invariant Zero-Shot Scene Graph Generation for 3D Scene Reasoning

IEEE Workshop/Winter Conference on Applications of Computer Vision
Scene understanding and reasoning has been a fundamental problem in 3D computer vision, requiring models to identify objects, their properties, and spatial or comparative relationships among the objects.
Vivek Madhavaram, Vartika Sengar, Arkadipta De, Charu Sharma   +3 more
semanticscholar   +1 more source

TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding

Trans. Mach. Learn. Res.
Scene graphs have proven to be highly effective for various scene understanding tasks due to their compact and explicit representation of relational information.
Quang P. M. Pham, Khoi T. N. Nguyen, Lan C. Ngo, Dezhen Song, Truong Do, T. Hy   +5 more
semanticscholar   +1 more source

Exploring Hierarchical Spatial Layout Cues for 3D Point Cloud Based Scene Graph Prediction

IEEE transactions on multimedia
3D scene graph prediction is important for intelligent agents to gather information and perceive semantics of their environments. However, constructing an effective graph is nontrivial given the complexity of natural scenes.
Mingtao Feng, Haoran Hou, L. Zhang, Yulan Guo, Hongshan Yu, Yaonan Wang, Ajmal Saeed Mian   +6 more
semanticscholar   +1 more source

FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts

Computer Vision and Pattern Recognition
Controllability plays a crucial role in the practical applications of 3D indoor scene synthesis. Existing works either allow rough language-based control, that is convenient but lacks fine-grained scene customization, or employ graph-based control, which
Tongyuan Bai, Wangyuanfan Bai, Dong Chen, Tieru Wu, Manyi Li, Rui Ma   +5 more
semanticscholar   +1 more source

MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation

AAAI Conference on Artificial Intelligence
Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry.
Zhifei Yang, Keyang Lu, Chao Zhang, Jiaxing Qi, Hanqi Jiang, Ruifei Ma, Shenglin Yin, Yifan Xu, Mingzhe Xing, Zhen Xiao, Jieyi Long, Xiangde Liu, Guangyao Zhai   +12 more
semanticscholar   +1 more source

3D Reconstruction of Graph Objects, Scenes, and Environments

2012
The purpose of this chapter is to provide a basic understanding of how three-dimensional (3D) statistical visual displays aid in education. The chapter seeks to discuss the importance of surface objects, scenes, and environments reconstructed to enhance the interpretation of charts. Further described are the different types of 3D charts available: bar,
Suhana Chikatla, Ukaiko Bitrus-Ojiambo
openaire   +1 more source

Aligned visual semantic scene graph for image captioning

Displays, 2022
Lixiang Li, Li Lixiang
exaly  

Learning to transfer focus of graph neural network for scene graph parsing

Pattern Recognition, 2021
Shuyou Zhang, Zhao Xinyue, Jianrong Tan   +2 more
exaly  

RelTR: Relation Transformer for Scene Graph Generation

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Michael Ying Yang, Bodo Rosenhahn, Yuren Cong   +2 more
exaly  

Atom correlation based graph propagation for scene graph generation

Pattern Recognition, 2022
Bingqian Lin, Xiaodan Liang
exaly