Enhancing Boundary Segmentation for Topological Accuracy with Skeleton-based Methods
University of Science and Technology Beijing（北京科技大学）；Beijing Advanced Innovation Center for Materials Genome Engineering（北京材料基因组创新中心）；School of Intelligence Science and Technology（智能科学与技术学院）；Shunde Innovation School（顺德创新学校）；Institute for Advanced Materials and Technology（先进材料与技术研究院）；Key Laboratory of Intelligent Bionic Unmanned Systems（智能仿生无人系统重点实验室）；Institute of Materials Intelligent Technology（材料智能技术研究院）；Liaoning Academy of Materials（辽宁省材料科学院）；School of Materials Science and Technology（材料科学与技术学院）
Topological consistency plays a crucial role in the task of boundary segmentation for reticular images, such as cell membrane segmentation in neuron electron microscopic images, grain boundary segmentation in material microscopic images and road segmentation in aerial images. In these fields, topological changes in segmentation results have a serious impact on the downstream tasks, which can even exceed the misalignment of the boundary itself. To enhance the topology accuracy in segmentation results, we propose the Skea-Topo Aware loss, which is a novel loss function that takes into account the shape of each object and topological significance of the pixels. It consists of two components. First, a skeleton-aware weighted loss improves the segmentation accuracy by better modeling the object geometry with skeletons. Second, a boundary rectified term effectively identifies and emphasizes topological critical pixels in the prediction errors using both foreground and background skeletons in the ground truth and predictions. Experiments prove that our method improves topological consistency by up to 7 points in VI compared to 13 state-of-art methods, based on objective and subjective assessments across three different boundary segmentation datasets. The code is available at https://github.com/clovermini/Skea_topo.
Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation
University of Bonn, Germany（波恩大学）；University College London, UK（伦敦大学学院）；Lamarr Institute for Machine Learning and Artificial Intelligence, Germany（拉马尔人工智能与机器学习研究所）
Department of Electrical Engineering, Indian Institute of Technology Ropar, India（电气工程系，印度理工学院罗帕尔学院）；Department of Computer Science and Engineering, Indian Institute of Technology Ropar, India（计算机科学与工程系，印度理工学院罗帕尔学院）；Artificial Intelligence and Data Engineering, Indian Institute of Technology Ropar, India（人工智能与数据工程，印度理工学院罗帕尔学院）
Slender Object Scene Segmentation in Remote Sensing Image Based on Learnable Morphological Skeleton with Segment Anything Model
School of Mathematical Sciences, Beijing Normal University（北京师范大学数学科学学院）；State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University（北京师范大学地理科学学部遥感科学国家重点实验室）
Cascaded multitask U-Net using topological loss for vessel segmentation and centerline extraction
Université de Reims Champagne Ardenne（兰斯香槟阿登大学）；Univ Lyon（里昂大学）；INSA-Lyon（里昂国立应用科学学院）；Université Claude Bernard Lyon 1（里昂第一大学）；UJM-Saint Etienne（圣埃蒂安大学）；CNRS（法国国家科学研究中心）；Inserm（法国国家健康与医学研究院）；CREATIS（CREATIS研究院）
University of Science and Technology of China（中国科学技术大学）；School of Biomedical Engineering（生物医学工程学院）；Naval Medical University（海军军医大学）；Second Affiliated Hospital（第二附属医院）；Suzhou Aerospace Information Research Institute（苏州航天信息研究院）
The XPRESS Challenge: Xray Projectomic Reconstruction -- Extracting Segmentation with Skeletons
Harvard Medical School（哈佛医学院）；Northeastern University（东北大学）；Harvard University（哈佛大学）；Boston College（波士顿学院）；MIT（麻省理工学院）；ESRF, The European Synchrotron（欧洲同步辐射装置）；Boston Children’s Hospital（波士顿儿童医院）
Spectral Scalpel: Amplifying Adjacent Action Discrepancy via Frequency-Selective Filtering for Skeleton-Based Action Segmentation
Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Shenzhen H&T Intelligent Control Co., Ltd.（深圳H&T智能控制有限公司）；Southern University of Science and Technology（南方科技大学）；Southeast University（东南大学）
Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation
State Key Laboratory of Robotics and Systems, Harbin Institute of Technology Shenzhen（哈尔滨工业大学深圳校区机器人学国家重点实验室）；e-Media Research Lab, KU Leuven（鲁汶大学电子媒体研究实验室）；Peng Cheng Laboratory（鹏城实验室）
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures
German Cancer Research Center (DKFZ)（德国癌症研究中心）；Heidelberg University（海德堡大学）；Helmholtz Information and Data Science School for Health（亥姆霍兹健康信息与数据科学学院）；Helmholtz Imaging（亥姆霍兹成像中心）
YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation
Southern University of Science and Technology（南方科技大学）；the University of Hong Kong（香港大学）；Jiaxing Research Institute, Southern University of Science and Technology（南方科技大学嘉兴研究院）
Segmentation of 3D pore space from CT images using curvilinear skeleton: application to numerical simulation of microbial decomposition
IRD（法国发展研究院）；UMMISCO（复杂系统数学与信息建模单元）；Cadi Ayyad University（卡迪·阿亚德大学）；Faculty of Sciences Semlalia（塞姆拉利亚科学学院）；LIB（自由研究所）；UFR Sciences et Techniques（科学与技术培训与研究单位）；University of Burgundy（勃艮第大学）；INRA（法国国家农业研究院）
Curve-Structure Segmentation from Depth Maps: A CNN-based Approach and Its Application to Exploring Cultural Heritage Objects
University of South Carolina（南卡罗来纳大学）；South Carolina Institute of Archaeology and Anthropology, University of South Carolina（南卡罗来纳大学南卡罗来纳考古与人类学研究所）；Center for Digital Humanities, University of South Carolina（南卡罗来纳大学数字人文中心）；Tianjin University（天津大学）
Skeleton-Guided Sparse Anchors for Rotated Instance Segmentation in Cell Microscopy
Aier Institute of Digital Ophthalmology and Visual Science（爱尔数字眼科学与视觉科学研究所）；Changsha Aier Eye Hospital（长沙爱尔眼科医院）；Shanghai Jiao Tong University（上海交通大学）；Nanyang Technological University（南洋理工大学）；Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University（复旦大学附属妇产科医院 生殖与发育研究院）
Enhancing Shape Perception and Segmentation Consistency for Industrial Image Inspection
School of Artificial Intelligence, Beijing University of Posts and Telecommunications（人工智能学院，北京邮电大学）；Ricoh Software Research Center (Beijing) Co., Ltd（Ricoh软件研究中心（北京）有限公司）
BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embedding
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University（上海交通大学图像处理与模式识别研究所）；Institute of Medical Robotics, Shanghai Jiao Tong University（上海交通大学医疗机器人研究院）；Department of Respiratory and Critical Care Medicine, Department of Respiratory Endoscopy, Shanghai Chest Hospital, Shanghai Engineering Research Center of Respiratory Endoscopy（上海市胸科医院呼吸与危重症医学科、呼吸内镜中心、上海市呼吸内镜工程技术研究中心）
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation
Department of Neuro-Oncology, Massachusetts General Hospital（麻省总医院神经肿瘤科）；MGH & BWH Center for Clinical Data Science（麻省总医院与布莱根妇女医院临床数据科学中心）；Department of Radiology, Massachusetts General Hospital（麻省总医院放射科）；Massachusetts General Hospital（麻省总医院）；NVIDIA（英伟达）
DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images
Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University（上海大学特种光纤与光接入网重点实验室）；Department of Computer Science, Johns Hopkins University（约翰斯·霍普金斯大学计算机科学系）；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）
