DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Sung-Hee | - |
dc.contributor.advisor | 이성희 | - |
dc.contributor.author | Lee, Myeongjin | - |
dc.date.accessioned | 2023-06-22T19:31:54Z | - |
dc.date.available | 2023-06-22T19:31:54Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032348&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/308307 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 문화기술대학원, 2023.2,[iii, 25 p. :] | - |
dc.description.abstract | In this paper, we propose a learning-based garment simulation algorithm that uses two consecutive networks to predict the deformation of loose-fit garments, preserving high details. The deformation is computed sequentially through low-frequency and high-frequency modules. First, the low-frequency module predicts the overall shape of the garments from the given body motion. Next, the high-frequency module estimates the high-resolution garments with detailed wrinkles by inferring the dynamics of the clothing, referred to the result of the previous module, the local information of the current garment mesh and some reference information. In addition, we improved the stability of rollout in inference time by mitigating the accumulation of errors over time using the scheduled sampling training method. The comparison shows that our method can estimate realistic and detailed garment meshes. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Cloth simulation▼aData-driven simulation▼aAnimation▼aNeural networks▼aMachine learning | - |
dc.subject | 의상 시뮬레이션▼a학습 기반 시뮬레이션▼a애니메이션▼a뉴럴 네트워크▼a머신 러닝 | - |
dc.title | Learning-based simulation of loose-fit garments | - |
dc.title.alternative | 루스핏 옷을 위한 학습 기반 시뮬레이션 연구 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :문화기술대학원, | - |
dc.contributor.alternativeauthor | 이명진 | - |
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