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Knowledge graphs meet multi-modal learning: A comprehensive survey
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
Foundations of spatial perception for robotics: Hierarchical representations and real-time systems
3D spatial perception is the problem of building and maintaining an actionable and
persistent representation of the environment in real-time using sensor data and prior …
persistent representation of the environment in real-time using sensor data and prior …
Hiker-sgg: Hierarchical knowledge enhanced robust scene graph generation
Being able to understand visual scenes is a precursor for many downstream tasks including
autonomous driving robotics and other vision-based approaches. A common approach …
autonomous driving robotics and other vision-based approaches. A common approach …
Task-driven causal feature distillation: Towards trustworthy risk prediction
Since artificial intelligence has seen tremendous recent successes in many areas, it has
sparked great interest in its potential for trustworthy and interpretable risk prediction …
sparked great interest in its potential for trustworthy and interpretable risk prediction …
Bridging Visual and Textual Semantics: Towards Consistency for Unbiased Scene Graph Generation
Scene Graph Generation (SGG) aims to detect visual relationships in an image. However,
due to long-tailed bias, SGG is far from practical. Most methods depend heavily on the …
due to long-tailed bias, SGG is far from practical. Most methods depend heavily on the …
RelBERT: Embedding Relations with Language Models
Many applications need access to background knowledge about how different concepts and
entities are related. Although Knowledge Graphs (KG) and Large Language Models (LLM) …
entities are related. Although Knowledge Graphs (KG) and Large Language Models (LLM) …
ESRA: a Neuro-Symbolic Relation Transformer for Autonomous Driving
Scene Graph Generation (SGG) is a powerful tool for autonomous vehicles to understand
their environment. In this paper, a novel one-stage neuro-symbolic architecture called nEuro …
their environment. In this paper, a novel one-stage neuro-symbolic architecture called nEuro …
Weakly-supervised video scene graph generation via unbiased cross-modal learning
Video Scene Graph Generation (VidSGG), which aims to detect the relations between
objects in a continuous spatio-temporal environment, has shown great potential in video …
objects in a continuous spatio-temporal environment, has shown great potential in video …
Refine and Redistribute: Multi-Domain Fusion and Dynamic Label Assignment for Unbiased Scene Graph Generation
Y Zang, Y Li, Y Gao, Y Guo, W Tang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Scene Graph Generation (SGG) plays an important role in enhancing visual image
comprehension. However, existing approaches often struggle to represent implicit …
comprehension. However, existing approaches often struggle to represent implicit …
Iterative learning with extra and inner knowledge for long-tail dynamic scene graph generation
Dynamic scene graphs have become a powerful tool for higher-level visual understanding
tasks, and the interest in dynamic scene graph generation (dynamic SGG) is grown over …
tasks, and the interest in dynamic scene graph generation (dynamic SGG) is grown over …