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3D Gaussian Splatting (3D-GS) has made a notable advancement in the field of neural rendering, 3D scene reconstruction, and novel view synthesis. Nevertheless, 3D-GS encounters the main challenge when it comes to accurately representing…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Rui Zhang , Tianyue Luo , Weidong Yang , Ben Fei , Jingyi Xu , Qingyuan Zhou , Keyi Liu , Ying He

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

Gaussian Splatting (GS) has emerged as an effective representation for photorealistic rendering, but the underlying geometry, material, and lighting remain entangled, hindering scene editing. Existing GS-based methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Kang Du , Zhihao Liang , Yulin Shen , Zeyu Wang

The reconstruction of 3D objects from calibrated photographs represents a fundamental yet intricate challenge in the domains of computer graphics and vision. Although neural reconstruction approaches based on Neural Radiance Fields (NeRF)…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Bang Du , Runfa Blark Li , Chen Du , Truong Nguyen

Recent advancements in photo-realistic novel view synthesis have been significantly driven by Gaussian Splatting (3DGS). Nevertheless, the explicit nature of 3DGS data entails considerable storage requirements, highlighting a pressing need…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Minye Wu , Tinne Tuytelaars

We propose Transmission-Reflection Gaussians (TR-Gaussians), a novel 3D-Gaussian-based representation for high-fidelity rendering of planar transmission and reflection, which are ubiquitous in indoor scenes. Our method combines 3D Gaussians…

Graphics · Computer Science 2025-11-18 Yong Liu , Keyang Ye , Tianjia Shao , Kun Zhou

Implicit neural representation has opened up new possibilities for inverse rendering. However, existing implicit neural inverse rendering methods struggle to handle strongly illuminated scenes with significant shadows and indirect…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Yanzhen Chen , Xinyu Gao , Yazhen Yuan , Yu Wu , Xiaowei Zhou , Xiaogang Jin

Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC) ray tracing poses challenges for modeling global…

Graphics · Computer Science 2025-06-09 Jiakai Sun , Weijing Zhang , Zhanjie Zhang , Tianyi Chu , Guangyuan Li , Lei Zhao , Wei Xing

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

3D Gaussian Splatting (3DGS) has recently emerged as a powerful explicit representation enabling fast, high-fidelity rendering, making it a promising foundation for closed-loop simulators and perception models in autonomous driving.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Kota Shimomura , Hidehisa Arai , Tsubasa Takahashi , Takayoshi Yamashita , Hironobu Fujiyoshi

Radiance field methods, such as Neural Radiance Field or 3D Gaussian Splatting, have emerged as seminal 3D representations for synthesizing realistic novel views. For practical applications, there is ongoing research on flexible scene…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Ji Hyun Seo , Byounhyun Yoo , Gerard Jounghyun Kim

Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among multiple objects. While natural illumination-based methods struggle to resolve this…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jiaye Wu , Saeed Hadadan , Geng Lin , Peihan Tu , Matthias Zwicker , David Jacobs , Roni Sengupta

In this paper, we present a novel differentiable point-based rendering framework to achieve photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla 3D Gaussians by associating extra properties, including…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jian Gao , Chun Gu , Youtian Lin , Zhihao Li , Hao Zhu , Xun Cao , Li Zhang , Yao Yao

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

Gaussian Splatting has recently become one of the most popular frameworks for photorealistic 3D scene reconstruction and rendering. While current rasterizers allow for efficient mappings of 3D Gaussian splats onto 2D camera views, this work…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Daniel Lieber , Alexander Mock , Nils Wandel

Implicit Neural Representations (INRs) approximate discrete data through continuous functions and are commonly used for encoding 2D images. Traditional image-based INRs employ neural networks to map pixel coordinates to RGB values,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Joanna Waczyńska , Tomasz Szczepanik , Piotr Borycki , Sławomir Tadeja , Thomas Bohné , Przemysław Spurek

One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and…

Graphics · Computer Science 2024-05-31 Artur Kasymov , Bartosz Czekaj , Marcin Mazur , Jacek Tabor , Przemysław Spurek

Recent advances in Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (3DGS) have achieved considerable performance in RGB scene reconstruction. However, multi-modal rendering that incorporates thermal infrared imagery remains largely…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Minseong Kweon , Janghyun Kim , Ukcheol Shin , Jinsun Park

Inverse rendering seeks to recover 3D geometry, surface material, and lighting from captured images, enabling advanced applications such as novel-view synthesis, relighting, and virtual object insertion. However, most existing techniques…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Chih-Hao Lin , Jia-Bin Huang , Zhengqin Li , Zhao Dong , Christian Richardt , Tuotuo Li , Michael Zollhöfer , Johannes Kopf , Shenlong Wang , Changil Kim

Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scene appearance, limiting flexibility for downstream editing.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Adrian Azzarelli , Nantheera Anantrasirichai , James Pollock , David R. Bull