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3D Gaussian Splatting (3DGS) has attracted significant attention for its high-quality novel view rendering, inspiring research to address real-world challenges. While conventional methods depend on sharp images for accurate scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Jungho Lee , Suhwan Cho , Taeoh Kim , Ho-Deok Jang , Minhyeok Lee , Geonho Cha , Dongyoon Wee , Dogyoon Lee , Sangyoun Lee

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Florian Hahlbohm , Linus Franke , Martin Eisemann , Marcus Magnor

3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhibit substantial appearance variations from different…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Jiayue Liu , Xiao Tang , Freeman Cheng , Roy Yang , Zhihao Li , Jianzhuang Liu , Yi Huang , Jiaqi Lin , Shiyong Liu , Xiaofei Wu , Songcen Xu , Chun Yuan

During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces. This…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yanyan Li , Chenyu Lyu , Yan Di , Guangyao Zhai , Gim Hee Lee , Federico Tombari

Reconstructing dynamic 3D scenes from monocular input is fundamentally under-constrained, with ambiguities arising from occlusion and extreme novel views. While dynamic Gaussian Splatting offers an efficient representation, vanilla models…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Fengzhi Guo , Chih-Chuan Hsu , Sihao Ding , Cheng Zhang

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull

In this work, we propose a novel clothed human reconstruction method called GaussianBody, based on 3D Gaussian Splatting. Compared with the costly neural radiance based models, 3D Gaussian Splatting has recently demonstrated great…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Mengtian Li , Shengxiang Yao , Zhifeng Xie , Keyu Chen

It is vital to infer a signed distance function (SDF) in multi-view based surface reconstruction. 3D Gaussian splatting (3DGS) provides a novel perspective for volume rendering, and shows advantages in rendering efficiency and quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Wenyuan Zhang , Yu-Shen Liu , Zhizhong Han

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

We propose PoseGaussian, a pose-guided Gaussian Splatting framework for high-fidelity human novel view synthesis. Human body pose serves a dual purpose in our design: as a structural prior, it is fused with a color encoder to refine depth…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Ju Shen , Chen Chen , Tam V. Nguyen , Vijayan K. Asari

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

While neural rendering has demonstrated impressive capabilities in 3D scene reconstruction and novel view synthesis, it heavily relies on high-quality sharp images and accurate camera poses. Numerous approaches have been proposed to train…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Lingzhe Zhao , Peng Wang , Peidong Liu

In this paper, we present an active exploration framework for high-fidelity 3D reconstruction that incrementally builds a multi-level uncertainty space and selects next-best-views through an uncertainty-driven motion planner. We introduce a…

Robotics · Computer Science 2025-11-26 Yan Li , Yingzhao Li , Gim Hee Lee

In this paper, we present a method to reconstruct the world and multiple dynamic humans in 3D from a monocular video input. As a key idea, we represent both the world and multiple humans via the recently emerging 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Inhee Lee , Byungjun Kim , Hanbyul Joo

Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic images. Therefore, security concerns arise regarding the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Davide Di Nucci , Riccardo Catalini , Guido Borghi , Roberto Vezzani

Real2Sim is becoming increasingly important with the rapid development of surgical artificial intelligence (AI) and autonomy. In this work, we propose a novel Real2Sim methodology, Instrument-Splatting, that leverages 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Shuojue Yang , Zijian Wu , Mingxuan Hong , Qian Li , Daiyun Shen , Septimiu E. Salcudean , Yueming Jin

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy. 3D Gaussian Splatting (3D-GS), a foundational point-based parametric 3D scene representation, models scenes as large sets of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Alex Hanson , Allen Tu , Vasu Singla , Mayuka Jayawardhana , Matthias Zwicker , Tom Goldstein

3D object reconstruction is important for semantic scene understanding. It is challenging to reconstruct detailed 3D shapes from monocular images directly due to a lack of depth information, occlusion and noise. Most current methods…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Ziwei Liao , Steven L. Waslander

The process of 3D scene reconstruction can be affected by numerous uncertainty sources in real-world scenes. While Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (GS) achieve high-fidelity rendering, they lack built-in mechanisms…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Marcus Klasson , Riccardo Mereu , Juho Kannala , Arno Solin