3D Gaussian Splatting (3DGS) enables real-time novel view synthesis with high visual quality. However, existing methods struggle with semi-transparent specular surfaces that exhibit both complex reflections and clear transmission, often producing blurry reflections or overly occluded transmission. To address this, we present RT-Splatting, a framework that disentangles each Gaussian's geometric occupancy from its optical opacity. This factorization yields a unified surface-volume scene representation with a single set of Gaussian primitives. Our hybrid renderer interprets this representation both as a surface to capture high-frequency reflections and as a volume to preserve clear transmission. To mitigate the ambiguity in jointly optimizing reflection and transmission, we introduce Specular-Aware Gradient Gating, which suppresses misleading gradients from highly specular regions into the transmission branch, effectively reducing distracting floaters. Experiments on challenging semi-transparent scenes show that RT-Splatting achieves state-of-the-art performance, delivering high-fidelity reflections and clear transmission with real-time rendering. Moreover, our factorization naturally enables flexible scene editing. The project page is available at https://sjj118.github.io/RT-Splatting.
Seeing Through Reflections: Advancing 3D Scene Reconstruction in Mirror-Containing Environments with Gaussian Splatting
School of Automation and Intelligent Sening, Shanghai Jiao Tong University（自动化与智能传感学院，上海交通大学）；Ningbo Artificial Intelligence Institute, Shanghai Jiao Tong University（宁波人工智能研究所，上海交通大学）
PolarGuide-GSDR: 3D Gaussian Splatting Driven by Polarization Priors and Deferred Reflection for Real-World Reflective Scenes
North China University of Technology（中国北方工业大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；University of Science and Technology Beijing（北京科技大学）
MaterialRefGS: Reflective Gaussian Splatting with Multi-view Consistent Material Inference
School of Software, Tsinghua University, Beijing, China（清华大学软件学院）；Center for AI and Robotics (CAIR), NYU Abu Dhabi, UAE（纽约大学阿布扎比分校人工智能与机器人中心）；Department of Computer Science, Wayne State University, Detroit, USA（韦恩州立大学计算机科学系）
Chongqing University（重庆大学）；MAIS, Institute of Automation, Chinese Academy of Sciences and UCAS（自动化研究所，中国科学院，UCAS）；King Abdullah University of Science and Technology (KAUST)（卡塔尔科学与技术大学）
RefGlass-GS: A UAV-Enabled Fusion Framework for Photorealistic, Semantic and Interactive Digitization of Reflective Glass Facades via Gaussian Splatting
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology（香港科技大学土木与环境工程系）；Department of Civil and Environmental Engineering, University of Maryland（马里兰大学土木与环境工程系）；Department of the Built Environment, National University of Singapore（新加坡国立大学环境与建筑系）；Department of Architecture and Civil Engineering, City University of Hong Kong（香港城市大学建筑与土木工程系）
Appearance Decomposition Gaussian Splatting for Multi-Traversal Reconstruction
Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis, Shanghai Jiao Tong University（上海交通大学自动化系，系统控制与信息处理教育部重点实验室，航空电子集成与航空系统综合国家重点实验室）
ProGS: Towards Progressive Coding for 3D Gaussian Splatting
College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机科学与软件工程学院）；Department of Computer Science, City University of Hong Kong（香港城市大学计算机科学系）；School of Electronic Information and Communications, Huazhong University of Science and Technology（华中科技大学电子信息与通信学院）
School of Electrical Engineering and Automation, Hefei University of Technology, and Engineering Technology Research Center of Industrial Automation Anhui Province, Hefei, Anhui 230009, China（合肥工业大学电气与自动化学院，安徽省工业自动化工程技术研究中心）；The University of Electro-Communications, Tokyo, Japan（东京电讯大学）；School of Computer Science and Technology, University of Science and Technology of China, Hefei, China（中国科学技术大学计算机科学与技术学院）；Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark（哥本哈根大学电子与计算机工程系）；Department of Computer Science and Electrical Engineering, University of Missouri–Kansas City, Kansas, USA（密苏里大学- Kansas 城市分校计算机科学与电气工程系）；School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China（合肥工业大学计算机科学与信息工程学院）
Fi-Gaussian: Frequency-Aware Implicit Gaussian Splatting for Single Image Dehazing
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）
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）
The reflections caused by common semi-reflectors, such as glass windows, can impact the performance of computer vision algorithms. State-of-the-art methods can remove reflections on synthetic data and in controlled scenarios. However, they are based on strong assumptions and do not generalize well to real-world images. Contrary to a common misconception, real-world images are challenging even when polarization information is used. We present a deep learning approach to separate the reflected and the transmitted components of the recorded irradiance, which explicitly uses the polarization prope…
Woven Fabric Capture with a Reflection-Transmission Photo Pair
Nankai University（南开大学）；Adobe Research（奥多比研究院）；Nanjing University of Science and Technology（南京理工大学）；School of Intelligence Science and Technology, Nanjing University（南京大学智能科学与技术学院）
