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The advent of neural 3D Gaussians 21 has recently brought about a revolution in the field of neural rendering, facilitating the generation of high-quality renderings at real-time speeds. However, the explicit and discrete repre-sentation encounters challenges when applied to scenes fea-turing reflective surfaces. In this paper, we present Gaus-sian Shader, a novel method that applies a simplified shading function on 3D Gaussians to enhance the neural ren-dering in scenes with reflective surfaces while preserving the training and rendering efficiency. The main challenge in applying the shading function lies in the accurate nor-mal estimation on discrete 3D Gaussians. Specifically, we proposed a novel normal estimation framework based on the shortest axis directions of 3D Gaussians with a deli-cately designed loss to make the consistency between the normals and the geometries of Gaussian spheres. Experiments show that GaussianShader strikes a commendable balance between efficiency and visual quality. Our method surpasses Gaussian Splatting 21 in PSNR on specular object datasets, exhibiting an improvement of 1.57dB. When compared to prior works handling reflective surfaces, such as Ref-NeRF 45, our optimization time is significantly accelerated (23h vs. 0.58h). Please click on our project web-site to see more results
Jiang et al. (Sun,) studied this question.