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Due to the real-time rendering performance, 3D Gaussian Splatting (3DGS) has emerged as the leading method for radiance field reconstruction. However, its reliance on spherical harmonics for color encoding inherently limits its ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yixin Yang , Bojian Wu , Yang Zhou , Hui Huang

3D Gaussian Splatting (3DGS) has demonstrated impressive capabilities in novel view synthesis. However, rendering reflective objects remains a significant challenge, particularly in inverse rendering and relighting. We introduce RTR-GS, a…

Graphics · Computer Science 2025-12-17 Yongyang Zhou , Fang-Lue Zhang , Zichen Wang , Lei Zhang

The 3D Gaussian splatting method has drawn a lot of attention, thanks to its high performance in training and high quality of the rendered image. However, it uses anisotropic Gaussian kernels to represent the scene. Although such…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yuanhao Gong , Lantao Yu , Guanghui Yue

Modeling of high-frequency outgoing radiance distributions has long been a key challenge in rendering, particularly for glossy material. Such distributions concentrate radiative energy within a narrow lobe and are highly sensitive to…

Graphics · Computer Science 2025-09-10 Jierui Ren , Haojie Jin , Bo Pang , Yisong Chen , Guoping Wang , Sheng Li

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

State-of-the-art techniques for 3D reconstruction are largely based on volumetric scene representations, which require sampling multiple points to compute the color arriving along a ray. Using these representations for more general inverse…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Benjamin Attal , Dor Verbin , Ben Mildenhall , Peter Hedman , Jonathan T. Barron , Matthew O'Toole , Pratul P. Srinivasan

We present a physics-based inverse rendering method that learns the illumination, geometry, and materials of a scene from posed multi-view RGB images. To model the illumination of a scene, existing inverse rendering works either completely…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Youming Deng , Xueting Li , Sifei Liu , Ming-Hsuan Yang

Many real-world materials are characterized by a glittery appearance. Reproducing this effect in physically based renderings is a challenging problem due to its discrete nature, especially in real-time applications which require a…

Graphics · Computer Science 2025-04-22 Tom Kneiphof , Reinhard Klein

Reconstructing complex reflections in real-world scenes from 2D images is essential for achieving photorealistic novel view synthesis. Existing methods that utilize environment maps to model reflections from distant lighting often struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Tao Xie , Xi Chen , Zhen Xu , Yiman Xie , Yudong Jin , Yujun Shen , Sida Peng , Hujun Bao , Xiaowei Zhou

Efficient shape reconstruction for surfaces with complex reflectance properties is crucial for real-time virtual reality. While 3D Gaussian Splatting (3DGS)-based methods offer fast novel view rendering by leveraging their explicit surface…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yufei Han , Bowen Tie , Heng Guo , Youwei Lyu , Si Li , Boxin Shi , Yunpeng Jia , Zhanyu Ma

Differentiable renderers provide a direct mathematical link between an object's 3D representation and images of that object. In this work, we develop an approximate differentiable renderer for a compact, interpretable representation, which…

Computer Vision and Pattern Recognition · Computer Science 2022-07-22 Leonid Keselman , Martial Hebert

The field of computer graphics was revolutionized by models such as Neural Radiance Fields and 3D Gaussian Splatting, displacing triangles as the dominant representation for photogrammetry. In this paper, we argue for a triangle comeback.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jan Held , Renaud Vandeghen , Adrien Deliege , Abdullah Hamdi , Silvio Giancola , Anthony Cioppa , Andrea Vedaldi , Bernard Ghanem , Andrea Tagliasacchi , Marc Van Droogenbroeck

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images. In order to achieve better decomposition, recent approaches attempt to model indirect illuminations reflected from different…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Haoqian Wu , Zhipeng Hu , Lincheng Li , Yongqiang Zhang , Changjie Fan , Xin Yu

Modeling reflections from 2D images is essential for photorealistic rendering and novel view synthesis. Recent approaches enhance Gaussian primitives with reflection-related material attributes to enable physically based rendering (PBR)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Wenyuan Zhang , Jimin Tang , Weiqi Zhang , Yi Fang , Yu-Shen Liu , Zhizhong Han

Implicit representations like Neural Radiance Fields (NeRF) showed impressive results for photorealistic rendering of complex scenes with fine details. However, ideal or near-perfectly specular reflecting objects such as mirrors, which are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Leif Van Holland , Ruben Bliersbach , Jan U. Müller , Patrick Stotko , Reinhard Klein

Implicit Neural Representation (INR) has demonstrated remarkable advances in the field of image representation but demands substantial GPU resources. GaussianImage recently pioneered the use of Gaussian Splatting to mitigate this cost,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zhaojie Zeng , Yuesong Wang , Chao Yang , Tao Guan , Lili Ju

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

We propose two novel ideas (adoption of deferred rendering and mesh-based representation) to improve the quality of 3D Gaussian splatting (3DGS) based inverse rendering. We first report a problem incurred by hidden Gaussians, where…

Graphics · Computer Science 2024-09-17 Euntae Choi , Sungjoo Yoo

The advent of neural and Gaussian-based radiance field methods have achieved great success in the field of novel view synthesis. However, specular reflection remains non-trivial, as the high frequency radiance field is notoriously difficult…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Keyang Ye , Qiming Hou , Kun Zhou