AIGS-Net: Compact Illumination Field Modeling via 2D Gaussian Splatting for Fast Low-Light Image Enhancement
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）；Herbert Wertheim College of Engineering, University of Florida（佛罗里达大学赫伯特·韦特海姆工程学院）；School of Mathematics and Statistics, Qingdao University（青岛大学数学与统计学院）；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）
Existing low-light image enhancement methods often face a bottleneck between the representation capacity of illumination-field modeling and computational complexity. To address this issue, this paper proposes an Adaptive Illumination Gaussian Splatting Network (AIGS-Net), an ultra-lightweight architecture for fast low-light enhancement. Unlike conventional static priors, AIGS-Net constructs an input-adaptive 2D Gaussian Splatting illumination field. The opacity of Gaussian basis functions is dynamically modulated by relative luminance statistics of the input image, and spatially varying illumination compensation is rendered through ordered alpha compositing. To guide adaptive illumination compensation efficiently, a zero-parameter nonlinear multiscale contextual encoding module is introduced to extract low-frequency structures and local contrast cues without additional convolutional weights. To suppress noise amplification and sensor-induced color bias, AIGS-Net integrates noise-mask estimation, locked single-channel Gamma mapping, cross-channel consistency regularization, and target color-alignment constraints. Experiments on LOL and LSRW benchmarks show that AIGS-Net improves detail recovery and color fidelity while requiring only approximately 40 learnable parameters, achieving an effective trade-off between enhancement quality and extreme inference efficiency.
Gaussian Light Field Splatting: A Physical Prior-Driven Vision Transformer for Unsupervised Low-Light Image Enhancement
College of Mechanical and Vehicle Engineering, Chongqing University（重庆大学机械与车辆工程学院）；Herbert Wertheim College of Engineering, University of Florida（佛罗里达大学赫伯特·韦特海姆工程学院）；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）
Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splatting
Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology（武汉光电国家研究中心，华中科技大学）；School of Computer Science, Wuhan University（武汉大学计算机学院）；Wuhan United Imaging Healthcare Surgical Technology Co., Ltd（武汉联影医疗手术技术有限公司）
Continuous Splatting meets Retinex: Continuous Gaussian Splatting and Implicit Reflectance Modeling for Low-Light Image Enhancement
College of Mechanical and Vehicle Engineering, Chongqing University（重庆大学机械与运载工程学院）；School of Engineering Science, University of Science and Technology of China（中国科学技术大学工程科学学院）；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）
Endo-4DGX: Robust Endoscopic Scene Reconstruction and Illumination Correction with Gaussian Splatting
Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China（香港中文大学电子工程系）；Shun Hing Institute of Advanced Engineering, CUHK, Hong Kong SAR, China（CUHK先进工程研究所）；City University of Hong Kong, Hong Kong, China（香港城市大学）；The University of Sydney, Sydney, NSW, Australia（悉尼大学）；Centre for Artificial Intelligence（人工智能中心）
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）
Physically Inspired Gaussian Splatting for HDR Novel View Synthesis
Department of Electrical and Computer Engineering, Northeastern University（东北大学电气与计算机工程系）；Khoury College of Computer Science, Northeastern University（东北大学Khoury计算机科学学院）
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）
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）
HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization
Sun Yat-sen University（中山大学）；Northeastern University（东北大学）；Guangdong Province Key Laboratory of Information Security Technology（广东省信息安全技术重点实验室）；Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, China（教育部机器智能与先进计算重点实验室）
CSS: Overcoming Pose and Scene Challenges in Crowd-Sourced 3D Gaussian Splatting
Beijing University of Posts and Telecommunications（北京邮电大学）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；China Unicom Smart City Research Institute（中国联通智慧城市研究院）
Point-Based 3D Reconstruction from Sparse Views under Known Illumination
Aalborg University（奥尔堡大学）；Centre for Software Technology, University of Southern Denmark（南丹麦大学软件技术中心）；Pioneer Centre for Artificial Intelligence（先锋人工智能中心）；Technical University of Denmark（丹麦技术大学）；Technische Universität Berlin（柏林工业大学）
Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague（捷克布拉格技术大学捷克信息学、机器人学与控制论研究所）；ETH Zurich（苏黎世联邦理工学院）；Google DeepMind（谷歌DeepMind）；Faculty of Electrical Engineering, Czech Technical University in Prague（捷克布拉格技术大学电气工程学院）
GS-IR: 3D Gaussian Splatting for Inverse Rendering
South China University of Technology（华南理工大学）；Tencent AI Lab（腾讯人工智能实验室）；School of Data Science, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）数据科学学院）
ROSGS: Relightable Outdoor Scenes With Gaussian Splatting
School of Information Science and Technology, North China University of Technology（信息科学与技术学院，中国北方工业大学）；Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences（移动计算与普适设备北京市重点实验室，中国科学院计算技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）；School of Computer Science and Informatics, Cardiff University（计算机科学与信息学院，卡迪夫大学）
