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modeling ambient scene dynamics for free view synthesis home teaser abstract method comparisons links bibtex modeling ambient scene dynamics for free view synthesis meng li shih 1 jia bin huang 2 3 changil kim 3 rajvi shah 3 johannes kopf 3 chen gao 3 1 university of washington 2 university of maryland college park 3 meta siggraph 2024 input video novel view time synthesis freeze time change view novel view time synthesis freeze view change time abstract we introduce a novel method for dynamic free view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience our method builds upon the recent advancements in 3d gaussian splatting 3dgs that can faithfully reconstruct complex static scenes previous attempts to extend 3dgs to represent dynamics have been confined to bounded scenes or require multi camera captures and often fail to generalize to unseen motions limiting their practical application our approach overcomes these constraints by leveraging the periodicity of ambient motions to learn the motion trajectory model coupled with careful regularization we also propose important practical strategies to improve the visual quality of the baseline 3dgs static reconstructions and to improve memory efficiency critical for gpu memory intensive learning we demonstrate high quality photorealistic novel view synthesis of several ambient natural scenes with intricate textures and fine structural elements method overview comparisons novel view time synthesis freeze time change view rodynrf liu et al 2023 4d gs wu et al 2023 ours novel view time synthesis freeze view change time rodynrf liu et al 2023 4d gs wu et al 2023 ours links code coming soon paper ablation study dataset coming soon bibtex inproceedings shihambgaus24 author meng li shih jia bin huang changil kim rajvi shah johannes kopf chen gao title modeling ambient scene dynamics for free view synthesis booktitle acm siggraph year 2024 copyright meng li shih 2024
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