PUGS: Zero-shot Physical Understanding with Gaussian Splatting
School of Computer Science and Technology, Tongji University（同济大学计算机科学与技术学院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；MGI Tech（华大科技）；Chulalongkorn University（朱拉隆功大学）；Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院）；Lightwheel AI（智驾科技）
Current robotic systems can understand the categories and poses of objects well. But understanding physical properties like mass, friction, and hardness, in the wild, remains challenging. We propose a new method that reconstructs 3D objects using the Gaussian splatting representation and predicts various physical properties in a zero-shot manner. We propose two techniques during the reconstruction phase: a geometry-aware regularization loss function to improve the shape quality and a region-aware feature contrastive loss function to promote region affinity. Two other new techniques are designed during inference: a feature-based property propagation module and a volume integration module tailored for the Gaussian representation. Our framework is named as zero-shot physical understanding with Gaussian splatting, or PUGS. PUGS achieves new state-of-the-art results on the standard benchmark of ABO-500 mass prediction. We provide extensive quantitative ablations and qualitative visualization to demonstrate the mechanism of our designs. We show the proposed methodology can help address challenging real-world grasping tasks. Our codes, data, and models are available at https://github.com/EverNorif/PUGS
Dehaze-GaussianImage: Zero-Shot Dehazing via Efficient 2D Gaussian Splatting Representation
College of Mechanical and Vehicle Engineering, Chongqing University（重庆大学机械与车辆工程学院）；Department of Electrical and Computer Engineering, Carnegie Mellon University（卡内基梅隆大学电气与计算机工程系）；National Innovation Center of Intelligent and Connected Vehicles（国家智能网联汽车创新中心）；School of Vehicle and Mobility, Tsinghua University（清华大学车辆与运载学院）
LGDWT-GS: Local and Global Discrete Wavelet-Regularized 3D Gaussian Splatting for Sparse-View Scene Reconstruction
National Institute of Standards and Technology（国家标准与技术研究院）；Department of Physics, Colorado State University（科罗拉多州立大学物理系）；Electrical Engineering Department, University of Colorado（科罗拉多大学电气工程系）
Light 'em Up: Enabling Few-Shot Low-Light 3D Gaussian Splatting with Multi-Scale Explicit Retinex Illumination Decoupling
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院航空航天信息研究所）；Key Laboratory of Target Cognition and Application Technology (TCAT)（目标认知与应用技术重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）；School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences（中国科学院大学电子电气与通信工程学院）；Shanghai Jiao Tong University（上海交通大学）
PLANA3R: Zero-shot Metric Planar 3D Reconstruction via Feed-Forward Planar Splatting
The Hong Kong University of Science and Technology（香港科技大学）；Ant Group（蚂蚁集团）；Wuhan University（武汉大学）；Zhejiang University（浙江大学）；The Pennsylvania State University（宾夕法尼亚州立大学）
MVPGS: Excavating Multi-view Priors for Gaussian Splatting from Sparse Input Views
School of Electronic and Computer Engineering, Peking University（北京大学电子与计算机工程学院）；School of Computer Science, University of Birmingham（伯明翰大学计算机学院）；Peng Cheng Laboratory（鹏城实验室）
Opacity-Gradient Driven Density Control for Compact and Efficient Few-Shot 3D Gaussian Splatting
Department of Computer Science and Physics, Wilfrid Laurier University（计算机科学与物理系，威尔弗里德·劳里尔大学）；Department of Computer Science（计算机科学系）；Physics, Wilfrid Laurier University（物理系，威尔弗里德·劳里尔大学）
CLIP-GS: Unifying Vision-Language Representation with 3D Gaussian Splatting
Institute of Information Science, Beijing Jiaotong University（北京交通大学信息科学学院）；National University of Singapore（新加坡国立大学）；Meituan（美团）；Georgia Institute of Technology（佐治亚理工学院）；Picsart AI Research (PAIR)（Picsart AI研究（PAIR））
AnySplat: Feed-forward 3D Gaussian Splatting from Unconstrained Views
University of Science and Technology of China（科学技术大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong（香港中文大学）；Brown University（布朗大学）；Shanghai Jiao Tong University（交通大学）；The University of Hong Kong（香港大学）
AD-GS: Anatomical Density-guided 3D Gaussian Splatting for Sparse-View Dental CBCT Reconstruction
Beijing University of Posts and Telecommunications（北京邮电大学）；Peking University Third Hospital（北京大学第三医院）；National Institute of Informatics（信息学研究所）；Peking University（北京大学）
You Need a Transition Plane: Bridging Continuous Panoramic 3D Reconstruction with Perspective Gaussian Splatting
Institute of Information Science, Beijing Jiaotong University（北京交通大学信息科学研究所）；Visual Intelligence +X International Cooperation Joint Laboratory of MOE（教育部视觉智能+X国际合作联合实验室）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）
3DSceneEditor: Controllable 3D Scene Editing with Gaussian Splatting
D Optical Metrology unit, Fondazione Bruno Kessler（3D光学测绘单元，布鲁诺·凯斯勒基金会）；Department of Information Engineering and Computer Science, University of Trento（信息工程与计算机科学系，特伦托大学）
GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning
School of Computer Science, Fudan University（复旦大学计算机科学学院）；School of Mechanical Engineering, Tongji University（同济大学机械工程学院）；Academy for Engineering and Technology, Fudan University（复旦大学工程技术研究院）
InterGSEdit: Interactive 3D Gaussian Splatting Editing with 3D Geometry-Consistent Attention Prior
MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics（信息产业部模式分析与机器智能重点实验室，计算机科学与技术学院，南京航空航天大学）；The Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology（教育部高维信息智能感知与系统重点实验室，计算机科学与工程学院，南京理工大学）
