Restoring incomplete or damaged 3D objects is crucial for cultural heritage preservation, occluded object reconstruction, and artistic design. Existing methods primarily focus on geometric completion, often neglecting texture restoration and struggling with relatively complex and diverse objects. We introduce Restore3D, a novel framework that simultaneously restores both the shape and texture of broken objects using multi-view images. To address limited training data, we develop an automated data generation pipeline that synthesizes paired incomplete-complete samples from large-scale 3D datasets. Central to Restore3D is a multi-view model, enhanced by a carefully designed Mask Self-Perceiver module with a Depth-Aware Mask Rectifier. The rectified masks learned by the self-perceiver guide an image integration and enhancement phase, helping retain observed shape and texture patterns while refining the generated regions and mitigating the low-resolution limitations of the base model, yielding high-resolution, semantically coherent, and view-consistent multi-view images. A coarse-to-fine reconstruction strategy is then employed to recover detailed textured 3D meshes from refined multi-view images. Experiments on synthetic and real broken-object benchmarks show that Restore3D improves multi-view restoration quality and textured-mesh reconstruction over representative inpainting, completion, and reconstruction baselines in the evaluated settings. Project Page: restore3dx.github.io
Attention-Guided Progressive Neural Texture Fusion for High Dynamic Range Image Restoration
Hong Kong Baptist University（香港浸会大学）；Institute of High Performance Computing, A*STAR（新加坡科技研究局高性能计算研究院）；vivo Mobile Communication Co. Ltd（维沃移动通信有限公司）；City University of Hong Kong（香港城市大学）；Nanyang Technological University（南洋理工大学）
Traffic Image Restoration under Adverse Weather via Frequency-Aware Mamba
School of Communication and Information Engineering, Shanghai University（上海大学通信与信息工程学院）；College of Electronic Science, Air Force Aviation University（空军航空大学电子科学学院）；Intelligent Visual Information Perception Laboratory, Institute of Advanced Technology, Nanjing University of Posts and Telecommunications（南京邮电大学先进技术研究院智能视觉信息感知实验室）；School of Computer Science and Technology, East China Normal University（华东师范大学计算机科学与技术学院）
Zero-Shot Video Restoration and Enhancement with Text-to-Image Latent Diffusion Models and Multi-Modal References
School of Electrical and Information Engineering, Tianjin University（天津大学电气自动化与信息工程学院）；Lappeenranta-Lahti University of Technology LUT（拉彭兰塔-拉赫蒂理工大学（LUT））
GTFMN: Guided Texture and Feature Modulation Network for Low-Light Image Enhancement and Super-Resolution
1 Graduate School of Engineering, Tohoku University, Sendai, Japan 2 Dept. of Radiology \& Biomedical Imaging, Yale University, New Haven, CT, USA 3 Dept. of Computer Science；Information Engineering, National Taiwan University, Taipei, Taiwan 4 Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan 5 Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan
MESA: A Training-Free Multi-Exemplar Deep Framework for Restoring Ancient Inscription Textures
Department of Computer Science and Engineering（计算机科学与工程系）；University of Ioannina（伊奥安纳大学）；Inria Paris-Rocquencourt（巴黎-罗克琴堡研究所）；Rajiv Gandhi University（拉朱·甘地大学）；Tsinghua University（清华大学）；Palmer Research Laboratories（帕勒尔研究实验室）
From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmark
State Key Laboratory of Novel Software Technology, Nanjing University（新型软件技术国家重点实验室，南京大学）；Department of Computer Science and Engineering, Michigan State University（计算机科学与工程系，密歇根州立大学）；School of Computer Science and Technology, Dalian University of Technology（计算机科学与技术学院，大连理工大学）
Bridging Degradation Discrimination and Generation for Universal Image Restoration
Institute of Medical Technology, Peking University（北京大学医学技术学院）；Biomedical Engineering Department, College of Future Technology, Peking University（北京大学未来技术学院生物医学工程系）；National Biomedical Imaging Center, Peking University（北京大学国家生物医学成像中心）；China Mobile Research Institute（中国移动研究院）
Image restoration quality assessment based on regional differential information entropy
Ningbo University（宁波大学）；Ningbo Institute of Industrial Technology, Chinese Academy of Sciences（中国科学院宁波工业技术研究院）；University of Chinese Academy of Sciences（中国科学院大学）
Harnessing Diffusion-Yielded Score Priors for Image Restoration
Shenzhen Institute of Advanced Technology, CAS（深圳先进技术研究院，中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）；The Chinese University of Hong Kong（香港中文大学）；SenseTime Research（商汤科技研究院）；Hong Kong Metropolitan University（香港 Metropolitan 大学）；INSAIT, Sofia University（INSAIT，索菲亚大学）；Shenzhen Institutes of Advanced Technology, CAS（深圳先进技术研究院，中国科学院）；Shenzhen University of Advanced Technology（深圳大学先进技术学院）
Progressive Semantic-Aware Style Transformation for Blind Face Restoration
The University of Hong Kong（香港大学）；Harbin Institute of Technology（哈尔滨工业大学）；DAMO Academy Alibaba Group（阿里巴巴达摩院）；Peking University（北京大学）；The Hong Kong Polytechnic University（香港理工大学）
COLA-Net: Collaborative Attention Network for Image Restoration
School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School（北京大学深圳研究生院电子与计算机工程学院）；School of Computer Science and Technology, Harbin Institute of Technology（哈尔滨工业大学计算机科学与技术学院）；Center for Biomedical Image Computing & Analytics, University of Pennsylvania（宾夕法尼亚大学生物医学图像计算与分析中心）
CMAMRNet: A Contextual Mask-Aware Network Enhancing Mural Restoration Through Comprehensive Mask Guidance
University of Macau（澳门大学）；Guangdong University of Technology（广东工业大学）；University of Chinese Academy of Sciences（中国科学院大学）；Shanghai Jiao Tong University（上海交通大学）；Shenzhen Polytechnic University（深圳职业技术大学）
Universal Face Restoration With Memorized Modulation
National Laboratory of Pattern Recognition, CASIA（中国科学院自动化研究所模式识别国家重点实验室）；Center for Excellence in Brain Science and Intelligence Technology, CAS（中国科学院脑科学与智能技术卓越创新中心）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
Data Driven Robust Image Guided Depth Map Restoration
Shanghai Jiao Tong University（上海交通大学）；University of Adelaide（阿德莱德大学）；University of Shanghai for Science and Technology（上海理工大学）；University of Technology, Sydney（悉尼科技大学）
SED-MVS: Segmentation-Driven and Edge-Aligned Deformation Multi-View Stereo with Depth Restoration and Occlusion Constraint
Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；School of Electrical Engineering and Computer Science, The University of Queensland（昆士兰大学电气工程与计算机科学学院）；Hunan Police Academy（湖南警察学院）；Cooperative MediaNet Innovation Center, Shanghai Jiao Tong University（上海交通大学协同媒体网络创新中心）；School of Information Science & Engineering, Lanzhou University（兰州大学信息科学与工程学院）；Agricultural Information Institute, Chinese Academy of Agricultural Sciences（中国农业科学院农业信息研究所）
6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving
Harbin Institute of Technology（哈尔滨工业大学）；Nanjing University of Science and Technology（南京理工大学）；National University of Defense Technology（国防科技大学）；Shandong Normal University（山东师范大学）；Qilu University of Technology（齐鲁工业大学）
