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Conference Paper Urban Scene Editing with Diffusion Model using Segmentation Mask
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Authors
Minho Park, Dong-oh Kang
Issue Date
2023-10
Citation
International Conference on Control, Automation and Systems (ICCAS 2023), pp.1881-1884
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.23919/ICCAS59377.2023.10316952
Abstract
With the growing interest in autonomous driving systems, the demand for real-world driving environment datasets is on the rise. However, traditional data collection methods are time-consuming and costly, and struggle to capture a variety of situations. This paper addresses these issues by proposing a diffusion-based image-to-image translation model that utilizes image segmentation label information. The model effectively separates parts of the image for translation while preserving other information. We validate the effectiveness of the proposed model on Cityscapes dataset, a widely-used urban scene dataset.
KSP Keywords
Autonomous driving system, Data Collection, Diffusion Model, Label information, Proposed model, Real-World driving, Translation Model, Urban scene, driving environment, image segmentation, traditional data