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Shape-guided Gaussian Splatting for Sparse-View X-ray 3D Reconstruction

Paper recorded by Signals 4 on 2026-09-09 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.CV · 计算机视觉 · first seen 2026-09-10

Abstract

Sparse-view X-ray 3D reconstruction is essential for reducing radiation exposure, but recovering a density field from a handful of X-ray projections is severely ill-posed. Recently, 3D Gaussian Splatting has achieved state-of-the-art performance in sparse-view reconstruction by representing the volume using explicit, optimized primitives, but it requires dozens of projected views. With fewer views

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#107 most recent of 237 cs.CV papers we have recorded · ↑ newer: Data-Driven Risk Fields for Safer End-to-End Autonomous Driving · ↓ older: Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervis
Cite this page: Shape-guided Gaussian Splatting for Sparse-View X-ray 3D Reconstruction: the #107 most recent of 237 cs.CV papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/shape-guided-gaussian-splatting-for-sparse-view-x-ray-3d-reconstruction.html
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