Hugging Face Trending Papers

PanoLess: Environment Reconstruction from Partial Reflective Views

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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.

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arXiv Computer Vision
Sep 18

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

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.

By Xiaobiao Du, Yida Wang, Cheng Bi, Kun Zhan, Xin Yu
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
arXiv Computer Vision
Sep 24

GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera

GLOW is a Global Illumination‑aware inverse rendering framework for indoor scenes captured with dynamic co‑located light and camera setups. It combines a neural implicit surface representation with a neural radiance cache to jointly optimize geometry and reflectance, while introducing a dynamic radiance cache and a surface‑angle‑weighted radiometric loss to handle near‑field motion, strong inter‑reflections, and specular highlights. Experiments demonstrate that GLOW significantly outperforms prior methods in estimating material reflectance under both natural and co‑located illumination.

By Jiaye Wu, Saeed Hadadan, Geng Lin, Peihan Tu, Auguste Gezalyan, Matthias Zwicker, David Jacobs, Roni Sengupta
Hugging Face Trending Papers
Jul 20

FF-ProCams: Feed-Forward Gaussian Splatting for Projector-Camera System

Projector-camera (ProCams) systems achieve active scene perception and controllable appearance manipulation via structured illumination, serving as a core infrastructure for spatial augmented reality, projection mapping, and surface reflectance acquisition. Existing inverse-rendering methods for ProCams deliver high-fidelity results but rely on time-consuming per-scene optimization, while mainstream feed-forward 3D reconstruction models produce baked appearance that cannot adapt to spatially varying projector illumination.