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Existing neural implicit surface reconstruction methods have achieved impressive performance in multi-view 3D reconstruction by leveraging explicit geometry priors such as depth maps or point clouds as regularization. However, the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Hanlin Chen , Chen Li , Yunsong Wang , Gim Hee Lee

In recent years, neural rendering methods such as NeRFs and 3D Gaussian Splatting (3DGS) have made significant progress in scene reconstruction and novel view synthesis. However, they heavily rely on preprocessed camera poses and 3D…

Graphics · Computer Science 2025-07-01 Chenhao Zhang , Yezhi Shen , Fengqing Zhu

Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accurately in 3DGS remains challenging due to the discrete nature of Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Yi He , Tao Wang , Yi Jin , Congyan Lang , Yidong Li , Haibin Ling

In this paper, we explore an open research problem concerning the reconstruction of 3D scenes from images. Recent methods have adopt 3D Gaussian Splatting (3DGS) to produce 3D scenes due to its efficient training process. However, these…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Beizhen Zhao , Yifan Zhou , Zijian Wang , Hao Wang

We propose two novel ideas (adoption of deferred rendering and mesh-based representation) to improve the quality of 3D Gaussian splatting (3DGS) based inverse rendering. We first report a problem incurred by hidden Gaussians, where…

Graphics · Computer Science 2024-09-17 Euntae Choi , Sungjoo Yoo

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

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

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Yuanyuan Gao , Yalun Dai , Hao Li , Weicai Ye , Junyi Chen , Danpeng Chen , Dingwen Zhang , Tong He , Guofeng Zhang , Junwei Han

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

3D Gaussian Splatting (3DGS) has made significant strides in novel view synthesis but is limited by the substantial number of Gaussian primitives required, posing challenges for deployment on lightweight devices. Recent methods address this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Zhengqing Gao , Dongting Hu , Jia-Wang Bian , Huan Fu , Yan Li , Tongliang Liu , Mingming Gong , Kun Zhang

3D Gaussian Splatting (GS) significantly struggles to accurately represent the underlying 3D scene geometry, resulting in inaccuracies and floating artifacts when rendering depth maps. In this paper, we address this limitation, undertaking…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Sadra Safadoust , Fabio Tosi , Fatma Güney , Matteo Poggi

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

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

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

3D Gaussian Splatting (3DGS) achieves state-of-the-art image quality and real-time performance in novel view synthesis but often suffers from a suboptimal spatial distribution of primitives. This issue stems from cloning-based…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Bartłomiej Baranowski , Stefano Esposito , Patricia Gschoßmann , Anpei Chen , Andreas Geiger

As 3D Gaussian Splatting (3D-GS) gains significant attention and its commercial usage increases, the need for watermarking technologies to prevent unauthorized use of the 3D-GS models and rendered images has become increasingly important.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Youngdong Jang , Hyunje Park , Feng Yang , Heeju Ko , Euijin Choo , Sangpil Kim

Depth maps are widely used in feed-forward 3D Gaussian Splatting (3DGS) pipelines by unprojecting them into 3D point clouds for novel view synthesis. This approach offers advantages such as efficient training, the use of known camera poses,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Duochao Shi , Weijie Wang , Donny Y. Chen , Zeyu Zhang , Jia-Wang Bian , Bohan Zhuang , Chunhua Shen

We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radiance, represented via per-band spherical harmonics, and optimized under a dual-loss…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Iris Zheng , Guojun Tang , Alexander Doronin , Paul Teal , Fang-Lue Zhang

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in 3D scene reconstruction. Beyond novel view synthesis, it shows great potential for multi-view surface reconstruction. Existing methods employ optimization-based…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Chensheng Dai , Shengjun Zhang , Min Chen , Yueqi Duan

The 3D Gaussian Splatting (3D-GS) is a novel method for scene representation and view synthesis. Although Scaffold-GS achieves higher quality real-time rendering compared to the original 3D-GS, its fine-grained rendering of the scene is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Chenyang Xu , XingGuo Deng , Rui Zhong