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Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, such optimization is prone to overfitting, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Meiying Gu , Jiawei Zhang , Jiahe Li , Xiaohan Yu , Haonan Luo , Jin Zheng , Xiao Bai

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but predominantly targets soft, deformable materials, leaving…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Bei Huang , Yixin Chen , Ruijie Lu , Gang Zeng , Hongbin Zha , Yuru Pei , Siyuan Huang

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 David Charatan , Sizhe Li , Andrea Tagliasacchi , Vincent Sitzmann

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

Recent advances in generative AI have accelerated the production of ultra-high-resolution visual content, posing significant challenges for efficient compression and real-time decoding on end-user devices. Inspired by 3D Gaussian Splatting,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Linfei Li , Lin Zhang , Zhong Wang , Ying Shen

This study addresses the challenge of accurately segmenting 3D Gaussian Splatting from 2D masks. Conventional methods often rely on iterative gradient descent to assign each Gaussian a unique label, leading to lengthy optimization and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Qiuhong Shen , Xingyi Yang , Xinchao Wang

Existing 3D Gaussian Splatting simplification methods commonly use importance scores, such as blending weights or sensitivity, to identify redundant Gaussians. However, these scores are not driven by visual error metrics, often leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Soonbin Lee , Yeong-Gyu Kim , Simon Sasse , Tomas M. Borges , Yago Sanchez , Eun-Seok Ryu , Thomas Schierl , Cornelius Hellge

Within colorectal cancer diagnostics, conventional colonoscopy techniques face critical limitations, including a limited field of view and a lack of depth information, which can impede the detection of precancerous lesions. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2024-08-19 Sierra Bonilla , Shuai Zhang , Dimitrios Psychogyios , Danail Stoyanov , Francisco Vasconcelos , Sophia Bano

Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can achieve fast and accurate 3D reconstruction. However, GS…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Natsuki Takama , Shintaro Ito , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki

Rendering complex reflection of real-world scenes using 3D Gaussian splatting has been a quite promising solution for photorealistic novel view synthesis, but still faces bottlenecks especially in rendering speed and memory storage. This…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Chang Liu , Hongliang Yuan , Lianghao Zhang , Sichao Wang , Jianwei Guo , Shi-Sheng Huang

Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, recent 2D Gaussian Splatting (GS) methods (\textit{e.g.},…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Tiantian Li , Xinjie Zhang , Xingtong Ge , Tongda Xu , Dailan He , Jun Zhang , Yan Wang

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. However, the 3D Gaussians learned by 3D-GS have ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Xu Hu , Yuxi Wang , Lue Fan , Chuanchen Luo , Junsong Fan , Zhen Lei , Qing Li , Junran Peng , Zhaoxiang Zhang

Constructing a 3D scene capable of accommodating open-ended language queries, is a pivotal pursuit, particularly within the domain of robotics. Such technology facilitates robots in executing object manipulations based on human language…

3D Gaussian Splatting (3DGS) provides an efficient method for high-quality scene reconstruction using anisotropic Gaussians. Recently, 3DGS-based methods have significantly improved the rendering quality of human avatars while enabling…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Hongzhe Liao , Chuhua Xian , Hongmin Cai , Haiyang Liu , Fa-Ting Hong

3D Gaussian Splatting has emerged as a transformative technique in novel view synthesis, primarily due to its high rendering speed and photorealistic fidelity. However, its memory footprint scales rapidly with scene complexity, often…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Keshav Gupta , Akshat Sanghvi , Shreyas Reddy Palley , Astitva Srivastava , Charu Sharma , Avinash Sharma

Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume reconstruction (SVR) methods are time-consuming and require multiple orthogonal stacks for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Yinsong Wang , Thomas Fletcher , Xinzhe Luo , Aine Travers Dineen , Rhodri Cusack , Chen Qin

Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Honggyu An , Jaewoo Jung , Mungyeom Kim , Chaehyun Kim , Minkyeong Jeon , Jisang Han , Kazumi Fukuda , Takuya Narihira , Hyuna Ko , Junsu Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

3D Gaussian Splatting has emerged as a powerful approach in novel view synthesis, delivering rapid training and rendering but at the cost of an ever-growing set of Gaussian primitives that strains memory and bandwidth. We introduce…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Hung Nguyen , An Le , Runfa Li , Truong Nguyen

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han
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