AI RESEARCH
Long-LRM++: Preserving Fine Details in Feed-Forward Wide-Coverage Reconstruction
arXiv CS.CV
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ArXi:2512.10267v2 Announce Type: replace Recent advances in generalizable Gaussian splatting (GS) have enabled feed-forward reconstruction of scenes from tens of input views. Long-LRM notably scales this paradigm to 32 input images at $950\times540$ resolution, achieving 360{\deg} scene-level reconstruction in a single forward pass. However, directly predicting millions of Gaussian parameters at once remains highly error-sensitive: small inaccuracies in positions or other attributes lead to noticeable blurring, particularly in fine structures such as text.