Brittle Fracture Animation with VQ-VAE-Based Generative Method

Simple item page
dc.contributor.authorHuang, Yuhangen_US
dc.contributor.authorKanai, Takashien_US
dc.contributor.editorZordan, Victoren_US
dc.date.accessioned2024-08-20T08:27:57Z
dc.date.available2024-08-20T08:27:57Z
dc.date.issued2024
dc.description.abstractWe propose a novel learning-based approach for predicting fractured shapes based on collision dynamics at run-time and seamlessly integrating realistic brittle fracture animations with rigid-body simulations. Our method utilizes BEM brittle fracture simulations to create training data. We introduce generative geometric segmentation, distinct from instance and semantic segmentation, to represent 3D fracture shapes. We adopt the concept of a neural discrete representation learning framework to optimize multiple discrete fractured patterns with a continuous latent code. Additionally, we propose a novel SDF-based cagecutting method to create fragments by cutting the original shape with the predicted fracture pattern. Our experimental results demonstrate that our approach can generate significantly more detailed brittle fractures compared to existing techniques, while reducing computational time typically when compared to traditional simulation methods at comparable resolutions.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animation - Posters
dc.identifier.doi10.2312/sca.20241163
dc.identifier.isbn978-3-03868-263-9
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/sca.20241163
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/sca20241163
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Animation; Neural networks; Learning latent representations
dc.subjectComputing methodologies → Animation
dc.subjectNeural networks
dc.subjectLearning latent representations
dc.titleBrittle Fracture Animation with VQ-VAE-Based Generative Methoden_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
sca20241163.pdf
Size:
558.37 KB
Format:
Adobe Portable Document Format
Download
Collections
SCA 2024 - Posters