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Related papers: Projecting Radiance Fields to Mesh Surfaces

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It is extremely challenging to create an animatable clothed human avatar from RGB videos, especially for loose clothes due to the difficulties in motion modeling. To address this problem, we introduce a novel representation on the basis of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zerong Zheng , Han Huang , Tao Yu , Hongwen Zhang , Yandong Guo , Yebin Liu

Searching for a unified scene representation remains a research challenge in computer graphics. Traditional mesh-based representations are unsuitable for dense, fuzzy elements, and introduce additional complexity for filtering and…

Graphics · Computer Science 2024-09-24 Yang Zhou , Songyin Wu , Ling-Qi Yan

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

Mesh processing pipelines are mature, but adapting them to newer non-mesh surface representations -- which enable fast rendering with compact file size -- requires costly meshing or transmitting bulky meshes, negating their core benefits…

Graphics · Computer Science 2025-08-19 Yuta Noma , Zhecheng Wang , Chenxi Liu , Karan Singh , Alec Jacobson

NeRF-based 3D-aware Generative Adversarial Networks (GANs) like EG3D or GIRAFFE have shown very high rendering quality under large representational variety. However, rendering with Neural Radiance Fields poses challenges for 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Florian Barthel , Arian Beckmann , Wieland Morgenstern , Anna Hilsmann , Peter Eisert

We introduce a training-free method for feature field rendering in Gaussian splatting. Our approach back-projects 2D features into pre-trained 3D Gaussians, using a weighted sum based on each Gaussian's influence in the final rendering.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Joji Joseph , Bharadwaj Amrutur , Shalabh Bhatnagar

We propose progressive radiance distillation, an inverse rendering method that combines physically-based rendering with Gaussian-based radiance field rendering using a distillation progress map. Taking multi-view images as input, our method…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Keyang Ye , Qiming Hou , Kun Zhou

3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. In recent times, some work has emerged that aims to extend…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Shijie Zhou , Haoran Chang , Sicheng Jiang , Zhiwen Fan , Zehao Zhu , Dejia Xu , Pradyumna Chari , Suya You , Zhangyang Wang , Achuta Kadambi

Differentiable rendering techniques like Gaussian Splatting and Neural Radiance Fields have become powerful tools for generating high-fidelity models of 3D objects and scenes. Their ability to produce both physically plausible and…

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

The 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi-view images, enabling real-time rendering. While point-based rasterization effectively reduces computational demands for…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Jiaze Li , Zhengyu Wen , Luo Zhang , Jiangbei Hu , Fei Hou , Zhebin Zhang , Ying He

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

Modeling wave properties of light is an important milestone for advancing physically-based rendering. In this paper, we propose complex-valued holographic radiance fields, a method that optimizes scenes without relying on intensity-based…

Graphics · Computer Science 2026-03-27 Yicheng Zhan , Dong-Ha Shin , Seung-Hwan Baek , Kaan Akşit

Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D representations with semantic information for downstream…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Mihnea-Bogdan Jurca , Remco Royen , Ion Giosan , Adrian Munteanu

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

Neural Radiance Fields achieve high-fidelity scene representation but suffer from costly training and rendering, while 3D Gaussian splatting offers real-time performance with strong empirical results. Recently, solutions that harness the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Grzegorz Wilczyński , Mikołaj Zieliński , Krzysztof Byrski , Joanna Waczyńska , Dominik Belter , Przemysław Spurek

This paper tackles the intricate challenge of object removal to update the radiance field using the 3D Gaussian Splatting. The main challenges of this task lie in the preservation of geometric consistency and the maintenance of texture…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Yuxin Wang , Qianyi Wu , Guofeng Zhang , Dan Xu

Reconstructing accurate surfaces with radiance fields has progressed rapidly, yet two promising explicit representations, 3D Gaussian Splatting and sparse-voxel rasterization, exhibit complementary strengths and weaknesses. 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Ting-Hsun Chi , Chu-Rong Chen , Chi-Tun Hsu , Hsuan-Ting Lin , Sheng-Yu Huang , Cheng Sun , Yu-Chiang Frank Wang

3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Safa C. Medin , Gengyan Li , Ruofei Du , Stephan Garbin , Philip Davidson , Gregory W. Wornell , Thabo Beeler , Abhimitra Meka

It is desirable to create 3D object models and 3D maps from 2D input images for applications such as navigation, virtual tourism, and urban planning. The traditional methods of creating 3D maps, (such as photogrammetry), require a large…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Sai Tarun Sathyan , Thomas B. Kinsman