Zhangji Lu

TR-GS achieves superior volumetric rendering quality in sparse-view CT by leveraging t-distribution primitives and a novel ray-confidence model, significantly reducing artifacts and uncertainty.

Achieve state-of-the-art atmospheric turbulence mitigation by modeling non-isoplanatic blur with Gaussian splatting, outperforming existing methods on both synthetic and real-world datasets.