Post-Training Semantic Lifting for 3D Gaussian Splatting: Separating Detector, Lifting and Representation Error
Paper recorded by Signals 4 on 2026-10-06 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-06 on arXiv · recorded by Signals 4 on 2026-10-07
Category: cs.CV · 计算机视觉 · first seen 2026-10-07
Abstract
The same Gaussian of a 3D Gaussian Splatting model is seen from many views, and these views do not always agree on the class it belongs to. The Gaussian may be occluded in some of them, and the confidence of the detector is not the same from one view to another. The ground truth, on the other hand, is given as an annotated mesh, because two training runs do not produce the same Gaussians. In this
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Cite this page: Post-Training Semantic Lifting for 3D Gaussian Splatting: Separating Detector, Lifting and Representation Error: the #341 most recent of 756 cs.CV papers we have recorded (as of 2026-10-06). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/post-training-semantic-lifting-for-3d-gaussian-splatting-separating-detector-lif.html
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