GBR: Generative Bundle Refinement for High-fidelity Gaussian Splatting with Enhanced Mesh Reconstruction
College of future information technology, Fudan University（未来信息科技学院，复旦大学）；School of Biomedical Engineering, Tsinghua University（生物医学工程学院，清华大学）；Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University（电磁波信息科学重点实验室（MoE），复旦大学）；Department of Automation, Tsinghua University（自动化系，清华大学）；MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University（人工智能重点实验室，人工智能研究院，上海交通大学）
Gaussian splatting has gained attention for its efficient representation and rendering of 3D scenes using continuous Gaussian primitives. However, it struggles with sparse-view inputs due to limited geometric and photometric information, causing ambiguities in depth, shape, and texture.
we propose GBR: Generative Bundle Refinement, a method for high-fidelity Gaussian splatting and meshing using only 4-6 input views. GBR integrates a neural bundle adjustment module to enhance geometry accuracy and a generative depth refinement module to improve geometry fidelity. More specifically, the neural bundle adjustment module integrates a foundation network to produce initial 3D point maps and point matches from unposed images, followed by bundle adjustment optimization to improve multiview consistency and point cloud accuracy. The generative depth refinement module employs a diffusion-based strategy to enhance geometric details and fidelity while preserving the scale. Finally, for Gaussian splatting optimization, we propose a multimodal loss function incorporating depth and normal consistency, geometric regularization, and pseudo-view supervision, providing robust guidance under sparse-view conditions. Experiments on widely used datasets show that GBR significantly outperforms existing methods under sparse-view inputs. Additionally, GBR demonstrates the ability to reconstruct and render large-scale real-world scenes, such as the Pavilion of Prince Teng and the Great Wall, with remarkable details using only 6 views.
GaMeS: Mesh-Based Adapting and Modification of Gaussian Splatting
Faculty of Mathematics and Computer Science（数学与计算机科学学院）；Jagiellonian University（雅盖隆大学）；Doctoral School of Exact and Natural Sciences（精确与自然科学博士学院）；Department of Engineering（工程学院）；University of Cambridge（剑桥大学）
SplattingAvatar: Realistic Real-Time Human Avatars with Mesh-Embedded Gaussian Splatting
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Prometheus Vision Technology Co., Ltd.（天演智视科技有限公司）；The Hong Kong University of Science and Technology（香港科技大学）
MeshSplats: Mesh-Based Rendering with Gaussian Splatting Initialization
Faculty of Mathematics and Computer Science, Jagiellonian University in Kraków（克拉科夫雅盖隆大学数学与计算机科学学院）；Department of Engineering, University of Cambridge（剑桥大学工程系）；IDEAS Research Institute（IDEAS研究所）
BridgeSplat: Bidirectionally Coupled CT and Non-Rigid Gaussian Splatting for Deformable Intraoperative Surgical Navigation
Computer Aided Medical Procedures, TU Munich, Munich, Germany（慕尼黑技术大学计算机辅助医疗程序部）；Department of General, Visceral, and Transplantation Surgery, Hospital of the LMU Munich, Ludwig-Maximilians-Universität (LMU), Munich, Germany（慕尼黑路德维希-马克西米利安大学（LMU）普通外科、 visceral外科及移植外科部门）；Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA（哈佛医学院布里特妇女医院）
University of Liverpool（利物浦大学）；Xi’an Jiaotong-Liverpool University（西交利物浦大学）；Universidad Antonio de Nebrija（安东尼奥·德·内布里哈大学）；ARIES Research Centre（ARIES研究中心）
Triangle Splatting+: Differentiable Rendering with Opaque Triangles
University of Liège（利根大学）；Simon Fraser University（西蒙弗雷泽大学）；University of Maryland（马里兰大学）；University of British Columbia（不列颠哥伦比亚大学）；University of Toronto（多伦多大学）；Adobe Research（Adobe研究）
Neural Surface Priors for Editable Gaussian Splatting
IDEAS NCBR；Adam Mickiewicz University（亚当·密茨凯维奇大学）；Wrocław University of Science and Technology（弗罗茨瓦夫理工大学）；Jagiellonian University（雅盖隆大学）；Tooploox；New Jersey Institute of Technology（新泽西理工学院）
MeshSplatting: Differentiable Rendering with Opaque Meshes
University of Liège（里耶克斯大学）；Simon Fraser University（西蒙弗雷泽大学）；University of Maryland（马里兰大学）；University of British Columbia（不列颠哥伦比亚大学）；University of Toronto（多伦多大学）；Adobe Research（Adobe研究院）
Comparative evaluation of photogrammetric reconstruction methods and 3D Gaussian Splatting for road surface roughness analysis
School of International Education, Hubei University of Technology（湖北工业大学国际教育学院）；School of Computer Science, Hubei University of Technology（湖北工业大学计算机科学学院）
GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Rendering
School of Intelligence Science and Technology, Peking University（北京大学智能科学与技术学院）；School of Computer Science and Engineering, Sun Yat-sen University（中山大学计算机科学与工程学院）；Wangxuan Institute of Computer Technology, Peking University（北京大学王轩计算机技术研究所）；State Key Laboratory of Multimedia Information Processing, Peking University（北京大学多媒体信息处理国家重点实验室）；State Key Laboratory of General Artificial Intelligence, Peking University（北京大学通用人工智能国家重点实验室）
RMAvatar: Photorealistic Human Avatar Reconstruction from Monocular Video Based on Rectified Mesh-embedded Gaussians
College of Computer Engineering, Jimei University（集美大学计算机工程学院）；National Institute for Data Science in Health and Medicine, Xiamen University（厦门大学健康与医学数据科学国家研究院）；The University of Texas at Dallas（德克萨斯大学达拉斯分校）；School of Informatics, Xiamen University（厦门大学信息学院）；BNU-HKBU United International College（北京师范大学-香港浸会大学联合国际学院）
Triangle Splatting for Real-Time Radiance Field Rendering
University of Liège（列日大学）；KAUST（阿卜杜拉国王科技大学）；University of Oxford（牛津大学）；Simon Fraser University（西蒙弗雷泽大学）；University of Toronto（多伦多大学）；Google DeepMind（谷歌DeepMind）
