MuRelSGG: Multimodal Relationship Prediction for Neurosymbolic Scene Graph Generation

MuRelSGG: Multimodal Relationship Prediction for Neurosymbolic Scene Graph Generation

Neurosymbolic Scene Graph Generation (SGG) is a promising approach that jointly leverages the perception capabilities of deep neural networks and the reasoning capabilities of symbolic techniques for scene understanding and visual reasoning. SGG systematically captures semantic components, including...

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Bibliographic Details
Main Authors: Muhammad Junaid Khan, Adil Masood Siddiqui, Hamid Saeed Khan, Faisal Akram, M. Jaleed Khan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Common sense knowledge
neurosymbolic integration
scene graph
scene understanding
visual reasoning
Online Access:https://ieeexplore.ieee.org/document/10925205/
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