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3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

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

Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Yunzhou Song , Heguang Lin , Jiahui Lei , Lingjie Liu , Kostas Daniilidis

We introduce abstract rendering, a method for computing a set of images by rendering a scene from a continuously varying range of camera positions. The resulting abstract image-which encodes an infinite collection of possible renderings-is…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yangge Li , Chenxi Ji , Xiangru Zhong , Huan Zhang , Sayan Mitra

3D Gaussian Splatting (3DGS) enables real-time, photorealistic novel view synthesis, making it a highly attractive representation for model-based video tracking. However, leveraging the differentiability of the 3DGS renderer "in the wild"…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Avigail Cohen Rimon , Amir Mann , Mirela Ben Chen , Or Litany

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Sparse-view 3D reconstruction is increasingly addressed with feed-forward splatting networks that predict explicit primitives directly from images. Yet most existing methods remain centered on Gaussian primitives and expose surfaces only…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Weijie Wang , Zimu Li , Jinchuan Shi , Zeyu Zhang , Botao Ye , Marc Pollefeys , Donny Y. Chen , Bohan Zhuang

Reconstructing 3D geometry and appearance from a sparse set of fixed cameras is a foundational task with broad applications, yet it remains fundamentally constrained by the limited viewpoints. We show that this bound can be broken by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Ryosuke Hirai , Kohei Yamashita , Antoine Guédon , Ryo Kawahara , Vincent Lepetit , Ko Nishino

3D Gaussian Splats (3DGS) have proven a versatile rendering primitive, both for inverse rendering as well as real-time exploration of scenes. In these applications, coherence across camera frames and multiple views is crucial, be it for…

The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representation compactness, reconstruction speed, and rendering fidelity. Previous solutions,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Roni Itkin , Noam Issachar , Yehonatan Keypur , Xingyu Chen , Anpei Chen , Sagie Benaim

Despite increasingly realistic image quality, recent 3D image generative models often operate on 3D volumes of fixed extent with limited camera motions. We investigate the task of unconditionally synthesizing unbounded nature scenes,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Lucy Chai , Richard Tucker , Zhengqi Li , Phillip Isola , Noah Snavely

We present a neural rendering framework that maps a voxelized scene into a high quality image. Highly-textured objects and scene element interactions are realistically rendered by our method, despite having a rough representation as an…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Konstantinos Rematas , Vittorio Ferrari

We propose $S^3$LAM, a novel RGB-D SLAM system that leverages 2D surfel splatting to achieve highly accurate geometric representations for simultaneous tracking and mapping. Unlike existing 3DGS-based SLAM approaches that rely on 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Ruoyu Fan , Yuhui Wen , Jiajia Dai , Tao Zhang , Long Zeng , Yong-jin Liu

Despite recent advances in leveraging generative prior from pre-trained diffusion models for 3D scene reconstruction, existing methods still face two critical limitations. First, due to the lack of reliable geometric supervision, they…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Junfeng Ni , Yixin Chen , Zhifei Yang , Yu Liu , Ruijie Lu , Song-Chun Zhu , Siyuan Huang

3D object detection within large 3D scenes is challenging not only due to the sparsity and irregularity of 3D point clouds, but also due to both the extreme foreground-background scene imbalance and class imbalance. A common approach is to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Oren Shrout , Yizhak Ben-Shabat , Ayellet Tal

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

We propose Camera Splatting, a novel view optimization framework for novel view synthesis. Each camera is modeled as a 3D Gaussian, referred to as a camera splat, and virtual cameras, termed point cameras, are placed at 3D points sampled…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Gahye Lee , Hyomin Kim , Gwangjin Ju , Jooeun Son , Hyejeong Yoon , Seungyong Lee

Simultaneous Localization and Mapping (SLAM) with 3D Gaussian Splatting (3DGS) enables fast, differentiable rendering and high-fidelity reconstruction across diverse real-world scenes. However, existing 3DGS-SLAM approaches handle…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Anh Thuan Tran , Jana Kosecka

Recent advancements in differentiable rendering and 3D reasoning have driven exciting results in novel view synthesis from a single image. Despite realistic results, methods are limited to relatively small view change. In order to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-13 Chris Rockwell , David F. Fouhey , Justin Johnson

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar
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