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Current Gaussian Splatting approaches are effective for reconstructing entire scenes but lack the option to target specific objects, making them computationally expensive and unsuitable for object-specific applications. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Marcel Rogge , Didier Stricker

In this paper, we propose RI3D, a novel 3DGS-based approach that harnesses the power of diffusion models to reconstruct high-quality novel views given a sparse set of input images. Our key contribution is separating the view synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Avinash Paliwal , Xilong Zhou , Wei Ye , Jinhui Xiong , Rakesh Ranjan , Nima Khademi Kalantari

3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of primitives. However, the semi-transparent nature of Gaussians prevents the application of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Brent Zoomers , Florian Hahlbohm , Joni Vanherck , Lode Jorissen , Marcus Magnor , Nick Michiels

Gaussian splatting enables fast novel view synthesis in static 3D environments. However, reconstructing real-world environments remains challenging as distractors or occluders break the multi-view consistency assumption required for…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Yihao Wang , Marcus Klasson , Matias Turkulainen , Shuzhe Wang , Juho Kannala , Arno Solin

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

Despite recent advances in single-object front-facing inpainting using NeRF and 3D Gaussian Splatting (3DGS), inpainting in complex 360{\deg} scenes remains largely underexplored. This is primarily due to three key challenges: (i)…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Shaoxiang Wang , Shihong Zhang , Christen Millerdurai , Rüdiger Westermann , Didier Stricker , Alain Pagani

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

Recent developments in 3D Gaussian Splatting have made significant advances in surface reconstruction. However, scaling these methods to large-scale scenes remains challenging due to high computational demands and the complex dynamic…

Graphics · Computer Science 2025-06-24 Shihan Chen , Zhaojin Li , Zeyu Chen , Qingsong Yan , Gaoyang Shen , Ran Duan

Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS often requires a large number of primitives to achieve high…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Haoran Wang , Guoxi Huang , Fan Zhang , David Bull , Nantheera Anantrasirichai

Recent advances in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made it standard practice to reconstruct 3D scenes from multi-view images. Removing objects from such 3D representations is a fundamental editing task…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Yonghao Zhao , Yupeng Gao , Jian Yang , Jin Xie , Beibei Wang

In large-scale scene reconstruction using 3D Gaussian splatting, it is common to partition the scene into multiple smaller regions and reconstruct them individually. However, existing division methods are occlusion-agnostic, meaning that…

Graphics · Computer Science 2025-12-02 Shiyong Liu , Xiao Tang , Zhihao Li , Yingfan He , Chongjie Ye , Jianzhuang Liu , Binxiao Huang , Shunbo Zhou , Xiaofei Wu

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman

Flexible industrial production systems will play a central role in the future of manufacturing due to higher product individualization and customization. A key component in such systems is the robotic grasping of known or unknown objects in…

Robotics · Computer Science 2025-03-18 Alexander Koebler , Ralf Gross , Florian Buettner , Ingo Thon

Reconstructing complete and animatable 3D human avatars from monocular videos remains challenging, particularly under severe occlusions. While 3D Gaussian Splatting has enabled photorealistic human rendering, existing methods struggle with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jinlong Fan , Shanshan Zhao , Liang Zheng , Jing Zhang , Yuxiang Yang , Mingming Gong

Rendering dynamic 3D human from monocular videos is crucial for various applications such as virtual reality and digital entertainment. Most methods assume the people is in an unobstructed scene, while various objects may cause the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Jingrui Ye , Zongkai Zhang , Yujiao Jiang , Qingmin Liao , Wenming Yang , Zongqing Lu

Generating and inserting new objects into 3D content is a compelling approach for achieving versatile scene recreation. Existing methods, which rely on SDS optimization or single-view inpainting, often struggle to produce high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Hongliang Zhong , Can Wang , Jingbo Zhang , Jing Liao

3D Gaussian Splatting has shown impressive novel view synthesis results; nonetheless, it is vulnerable to dynamic objects polluting the input data of an otherwise static scene, so called distractors. Distractors have severe impact on the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Paul Ungermann , Armin Ettenhofer , Matthias Nießner , Barbara Roessle

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

Novel view synthesis from unconstrained in-the-wild images remains a meaningful but challenging task. The photometric variation and transient occluders in those unconstrained images make it difficult to reconstruct the original scene…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Dongbin Zhang , Chuming Wang , Weitao Wang , Peihao Li , Minghan Qin , Haoqian Wang

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
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