AI RESEARCH
LTGS: Long-Term Gaussian Scene Chronology From Sparse View Updates
arXiv CS.CV
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ArXi:2510.09881v2 Announce Type: replace Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. However, the everyday environment experiences frequent scene changes, which require dense observations, both spatially and temporally, that an ordinary setup cannot cover. We propose long-term Gaussian scene chronology from sparse-view updates, coined LTGS, an efficient scene representation that can embrace everyday changes from highly under-constrained casual captures.