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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

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

This paper presents our approach to the NTIRE 2026 3D Restoration and Reconstruction Challenge (Track 1), which focuses on reconstructing high-quality 3D representations from degraded multi-view inputs. The challenge involves recovering…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yuhao Liu , Dingju Wang , Ziyang Zheng

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yujie Wang , Praneeth Chakravarthula , Baoquan Chen

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Saptarshi Neil Sinha , Holger Graf , Michael Weinmann

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

Open-vocabulary querying in 3D space is crucial for enabling more intelligent perception in applications such as robotics, autonomous systems, and augmented reality. However, most existing methods rely on 2D pixel-level parsing, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Yiren Lu , Yunlai Zhou , Yiran Qiao , Chaoda Song , Tuo Liang , Jing Ma , Huan Wang , Yu Yin

We introduce ODE-GS, a novel approach that integrates 3D Gaussian Splatting with latent neural ordinary differential equations (ODEs) to enable future extrapolation of dynamic 3D scenes. Unlike existing dynamic scene reconstruction methods,…

Graphics · Computer Science 2026-04-28 Daniel Wang , Patrick Rim , Tian Tian , Dong Lao , Alex Wong , Ganesh Sundaramoorthi

We introduce an image upscaling technique tailored for 3D Gaussian Splatting (3DGS) on lightweight GPUs. Compared to 3DGS, it achieves significantly higher rendering speeds and reduces artifacts commonly observed in 3DGS reconstructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Simon Niedermayr , Christoph Neuhauser Rüdiger Westermann

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xi Liu , Chaoyi Zhou , Siyu Huang

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

Recently, 3D Gaussian Splatting (3D-GS) has emerged, showing real-time rendering speeds and high-quality results in static scenes. Although 3D-GS shows effectiveness in static scenes, their performance significantly degrades in real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Wongi Park , Myeongseok Nam , Siwon Kim , Sangwoo Jo , Soomok Lee

The semantic synthesis of unseen scenes from multiple viewpoints is crucial for research in 3D scene understanding. Current methods are capable of rendering novel-view images and semantic maps by reconstructing generalizable Neural Radiance…

Graphics · Computer Science 2025-05-09 Feng Xiao , Hongbin Xu , Wanlin Liang , Wenxiong Kang

We present TrackGS, a novel method to integrate global feature tracks with 3D Gaussian Splatting (3DGS) for COLMAP-free novel view synthesis. While 3DGS delivers impressive rendering quality, its reliance on accurate precomputed camera…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Dongbo Shi , Shen Cao , Lubin Fan , Bojian Wu , Jinhui Guo , Ligang Liu , Renjie Chen

3D Gaussian Splatting (3DGS) delivers high-fidelity real-time rendering but suffers from geometric and photometric degradations under sparse-view constraints. Current generative restoration approaches are often limited by insufficient…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Xinliang Wang , Yifeng Shi , Zhenyu Wu

The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations. While demonstrating the potential for real-time rendering, 3D-GS encounters rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Kerui Ren , Lihan Jiang , Tao Lu , Mulin Yu , Linning Xu , Zhangkai Ni , Bo Dai

3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit methods built on Signed Distance Fields or occupancy, 3DGS lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Diego Gomez , Antoine Guédon , Nissim Maruani , Bingchen Gong , Maks Ovsjanikov

Gaussian Splatting (GS) has recently emerged as a promising technique for 3D object reconstruction, delivering high-quality rendering results with significantly improved reconstruction speed. As variants continue to appear, assessing the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Tianang Chen , Jian Jin , Shilv Cai , Zhuangzi Li , Weisi Lin

3D Gaussian Splatting (GS) enables fast and high-quality scene reconstruction, but it lacks an object-consistent and semantically aware structure. We propose Split&Splat, a framework for panoptic scene reconstruction using 3DGS. Our…

Graphics · Computer Science 2026-02-04 Leonardo Monchieri , Elena Camuffo , Francesco Barbato , Pietro Zanuttigh , Simone Milani

Despite recent successes in novel view synthesis using 3D Gaussian Splatting (3DGS), modeling scenes with sparse inputs remains a challenge. In this work, we address two critical yet overlooked issues in real-world sparse-input modeling:…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yingji Zhong , Zhihao Li , Dave Zhenyu Chen , Lanqing Hong , Dan Xu
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