Graph-Based Label Propagation

Latest papers

18 papers3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Anchored Slice Propagation with Boundary Transport for 3D CT Segmentation from Three Orthogonal Annotated Slices
Nov 3, 2026Tushar Kataria, Md Rakibul Haque, Shireen Y. ElhabianMedical Image Segmentation 3D Medical Image Segmentation
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA · Kahlert School of Computing, University of Utah, Salt Lake City, USA
When Links Mislead: Label-Free Structural Polarity for Zero-Shot Classification of Web Pages
Oct 30, 2026Hanshuai Cui, Zhiqing Tang, Zhi Yao +2Zero-Shot Text Classification Graph-Based Label Propagation
School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China · Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai 519087, China · College of Computing and Data Science, Nanyang Technological University, Singapore
Revisiting Simple Baselines for Relational Deep Learning
Oct 14, 2026Viet The Nguyen, Vijay Prakash Dwivedi, Gunther GustGraph-Based Label Propagation Relational Deep Learning
University of Würzburg · Seamless Labs, Inc. · Stanford University
What Egocentric Video Embeddings Encode and How to Combine Them with Inertial Sensors for Human Activity Recognition
Oct 9, 2026Kansuke HabanoGraph-Based Label Propagation Human Activity Recognition
Independent Researcher, Japan
Propagate, Then Sharpen: Post-Hoc Refinement of Frozen Node Classifiers
Sep 28, 2026Preben Johnsen Bentdal, Nello Blaser, Xue-Cheng TaiGraph-Based Semi-Supervised Learning Classification
Department of Informatics, University of Bergen · Norwegian Research Centre (NORCE)
COSTA: A Cluster-Centric Paradigm for Annotation-Free Open-Set Semantic Segmentation of Aerial Point Clouds with Domain Shifts
Aug 19, 2026Yanghong Lin, Li Fang, Tianyu Li +2Graph-Based Label Propagation 3D Point Cloud Segmentation
Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, 350108, Fujian, China. · Spatial Intelligence and Urban Computing, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, Fujian, China. · State Key Lab for Ecological Security of Regions and Cities, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, Fujian, China. +2
SSR: Similarity-Shift Refinement for Training-Free Object-Centric Masks
Aug 2, 2026Xiaoqian Lu, Guangfu GuoGraph-Based Label Propagation Image Segmentation
University of Ottawa · Clemson University
A Near-Linear-Time Solver for Graph $p$ -Laplacian Semi-Supervised Learning via Continuation in $p$
Jul 3, 2026Oren E. LivneGraph-Based Semi-Supervised Learning Semi-Supervised Learning
Pine Birch Analytics, Churchville, PA
Multi-Label Node Classification with Label Influence Propagation
Jul 1, 2026Yifei Sun, Zemin Liu, Bryan Hooi +4Graph-Based Label Propagation Multi-Label Classification
Zhejiang University · National University of Singapore · Capital One +1
MaskedFOP: Polyglot Speaker Identification under Missing Visual Modality via Cascaded Graph Label Propagation
Jun 12, 2026Ayoub Elkhouzari, Youssef Iraqi, Loubna MekouarMissing-Modality Learning Graph-Based Label Propagation
College of Computing, University Mohammed VI Polytechnic
Towards Robust and Scalable Density-based Clustering via Graph Propagation
May 1, 2026Yingtao Zheng, Hugo Phibbs, Ninh PhamGraph-Based Label Propagation Clustering
School of Computer Science, University of Auckland, New Zealand. · Department of Mathematics and Computer Science, University of Southern Denmark, Denmark.
F\textsuperscript{2}LP-AP: Fast & Flexible Label Propagation with Adaptive Propagation Kernel
Apr 22, 2026Yutong Shen, Ruizhe Xia, Jingyi Liu +1Graph-Based Semi-Supervised Learning Semi-Supervised Learning
Beijing University of Technology
MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models
Apr 16, 2026Ruiqi Wang, Qi Yu, Jie Ma +1Graph-Based Label Propagation Land Cover Classification
School of Information Science and Technology, Beijing Foreign Studies University, Beijing 100089, China
DynLP: Parallel Dynamic Batch Update for Label Propagation in Semi-Supervised Learning
Apr 8, 2026S M Shovan, Arindam Khanda, S M Ferdous +2GPU Acceleration Graph-Based Label Propagation
Missouri University of Science and Technology, Rolla, MO, USA · Pacific Northwest National Laboratory, USA
PEARL: Geometry Aligns Semantics for Training-Free Open-Vocabulary Semantic Segmentation
Mar 23, 2026Gensheng Pei, Xiruo Jiang, Xinhao Cai +3Graph-Based Label Propagation Open-Vocabulary Semantic Segmentation
Department of Electrical and Computer Engineering, Sungkyunkwan University · School of Computing and Artificial Intelligence, Southwest Jiaotong University · School of Computer Science and Engineering, Nanjing University of Science and Technology
BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop
Mar 2, 2026Chao Chen, Xujia Li, Dongsheng Hong +4Graph-Based Label Propagation Graph Representation Learning
Harbin Institute of Technology (Shenzhen), Guangdong, China · The Hong Kong University of Science and Technology, Hong Kong SAR, China · Fuzhou University, Fujian, China +1
Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size
Oct 6, 2025Farid Bozorgnia, Vyacheslav Kungurtsev, Shirali Kadyrov +1Over-Smoothing in GNNs Graph-Based Semi-Supervised Learning
GLL: A Differentiable Graph Learning Layer for Neural Networks
Dec 11, 2024Jason Brown, Bohan Chen, Harris Hardiman-Mostow +2Graph-Based Label Propagation Graph-Based Semi-Supervised Learning
Department of Mathematics University of California, Los Angeles Los Angeles, CA 90095, USA · Computing + Mathematical Sciences (CMS) Department California Institute of Technology Pasadena, CA 91125, USA · School of Mathematics University of Minnesota Minneapolis, MN 55455, USA

Nov 3, 2026J/K move · Enter open · S save

Anchored Slice Propagation with Boundary Transport for 3D CT Segmentation from Three Orthogonal Annotated Slices

Tushar Kataria, Md Rakibul Haque, Shireen Y. Elhabian

Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, USA · Kahlert School of Computing, University of Utah, Salt Lake City, USA

Medical Image Segmentation 3D Medical Image Segmentation Boundary-Aware Segmentation Multi-Organ Segmentation Computed Tomography Graph-Based Label Propagation

Open paper AskPDF arXiv

Sli2Vol propagates a binary mask through affinities between adjacent slices, but an error can persist because each prediction becomes the input to the next step. Three orthogonal annotations reduce dependence on any one chain, yet they offer more than three starting masks: where a chain crosses another annotated plane, the correct label is already known. Those labels could correct drift during propagation and indicate how much to trust each chain at fusion. Between annotated planes, the information carried by the chain may matter as well. A binary mask records foreground membership but discards distance to the boundary, a cue that could help follow gradual shape changes between slices.We address these two sources of error with a fixed pretrained affinity backbone. We anchor each chain by correcting its prediction where it crosses another annotated plane, then use its agreement with those labels to weight fusion. We compare this anchored mask with two ways of transporting boundary geometry: a truncated signed-distance field (SDF) propagated by dense affinity averaging, and a contour whose vertices follow motion cues from the same affinity. The contour tracker starts from a hand-crafted rule and learns a motion correction from supervoxel pseudo-objects in 506 CT volumes, without manual organ labels. On 2,091 held-out structure instances from approximately 403 CT scans spanning 17 abdominal structures, anchoring raises mean Dice from 0.737 with orthogonal mask propagation to 0.769 and improves every structure. Beyond the anchored mask, learned contour tracking improves Dice by 5.7% for the esophagus and 5.9% for the postcava, while SDF transport improves right-adrenal Dice by 2.8%. The anchored methods have similar mean Dice (0.769--0.772); contour tracking performs worse on the kidneys, stomach, and hepatic vessel tree.