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Overview
The workshop focuses on the topic of scene graphs and graph representation learning for visual perception applications in different domains. Through a series of keynote talks, the audience will learn about defining, generating and predicting scene graphs, as well as about employing them for other tasks. Oral presentations of accepted submissions to the workshop will further enrich discussed topics with state-of-the-art advancements and engage the community. The objective is for attendees to learn about current developments and application domains of scene graphs and graph representation learning, as well as to draw inspiration and identify commonalities across these domains. Furthermore, this workshop will create an opportunity to discuss limitations, challenges, and next steps from research, practical, and ethical perspectives.
Topics
Scene graph generation and prediction
Graph representation learning
Image generation and manipulation using scene graphs
Evaluation metrics for scene graphs
Common-sense graphs and knowledge graphs
Applications of graph theory and scene graphs to: computer vision, robotic perception, medical imaging, AR/VR, computer graphics, autonomous driving, etc.
Important Dates and Details
Updates will be posted on twitter via the workshop account.
Apply to be part of Program Committee by: July 15th, 2023 using this link.
Paper submission deadline: July 30th, 2023 at 11:59 pm AoE using this CMT portal.
Workshop: October 2nd, at ICCV 2023, Paris, France
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