arXiv Computer Vision By Xiaobiao Du, Yida Wang, Cheng Bi, Kun Zhan, Xin Yu

RGS: Reflection-aware Gaussian Splatting via Learning Geometry Continuity for Reflective Objects

Read the original on arXiv Computer Vision →

The paper introduces Reflection-aware Gaussian Splatting (RGS), a physically-based deferred rendering framework that improves novel view synthesis for reflective objects. RGS leverages a powerful 3D foundation model to provide a strong geometric prior and employs cross-view shape consistency regularization to prevent surface collapse and reduce geometric hollows. Additionally, a reflection-aware densification strategy captures specular variations across views, resulting in higher-quality renderings of reflective objects.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

arXiv AI
Jun 3

Ref-DGS: Reflective Dual Gaussian Splatting

arXiv:2603. 07664v3 Announce Type: replace-cross Abstract: The reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface reconstruction and novel view synthesis.

By Ningjing Fan, Yiqun Wang, Dongming Yan, Peter Wonka
Hugging Face Trending Papers
Jul 28

PanoLess: Environment Reconstruction from Partial Reflective Views

Reflections from shiny objects and glass facades naturally extend the field of view of a camera, capturing the surrounding environment without the need to pan the camera or acquire a full panorama. We propose PanoLess, a Gaussian-splat-based framework that reconstructs the surrounding environment as a distant illumination map from images captured on only one side of a reflective surface.