AI RESEARCH
Learn2Splat: Extending the Horizon of Learned 3DGS Optimization
arXiv CS.CV
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ArXi:2605.15760v1 Announce Type: new 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purpose and not tailored to the structure of the problem. In particular, they produce independent parameter updates that do not capture the structural and spatial relationships within a scene, leading to inefficient optimization and slow convergence. Recent works