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https://github.com/subeeshvasu/Awsome_Delineation


https://github.com/subeeshvasu/Awsome_Delineation

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README 

        
# Awsome Delineation



A curated list of resources for Delineation



**Papers**



+ 1989-CVGIP - Digital topology: Introduction and survey. [[Paper]](https://www.sciencedirect.com/science/article/pii/0734189X89901473)



+ 1994-CVGIP - Building skeleton models via 3-D medial surface axis thinning algorithms. [[Paper]](https://www.sciencedirect.com/science/article/pii/S104996528471042X)



+ 1994-CVGIP -  On topology preservation in 3D thinning. [[Paper]](https://www.sciencedirect.com/science/article/abs/pii/S1049966084710230)



+ 1995-IJPRAI - On topology preservation in 2-D and 3-D thinning. [[Paper]](https://www.sciencedirect.com/science/article/abs/pii/S1049966084710230)



+ 1995-PR - A skeletonization algorithm by maxima tracking on euclidean distance transform. [[Paper]](https://www.sciencedirect.com/science/article/pii/003132039400104T)



+ 1995-IVC - Skeletonization using an extended euclidean distance transform. [[Paper]](https://www.sciencedirect.com/science/article/pii/026288569599723E)



+ 1996-TPAMI - Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation. [[Paper]](https://ieeexplore.ieee.org/document/341090)



+ 2000-MVA - Automatic Extraction of Roads from Aerial Images Based on Scale Space and Snakes. [[Paper]](http://www.irisa.fr/vista/Papers/2000_mva_laptev.pdf)



+ 2002-PRL - A 3-subiteration 3D thinning algorithm for extracting medial surfaces. [[Paper]](https://www.sciencedirect.com/science/article/pii/S0167865501001428)



+ 2003-TPAMI - A topology preserving level set method for geometric deformable models. [[Paper]](https://core.ac.uk/download/pdf/22876105.pdf)



+ 2004-TMI - Ridge-based vessel segmentation in color images of the retina. [[Paper]](https://ieeexplore.ieee.org/document/1282003)



+ 2004-CSUR - A review of vessel extraction techniques and algorithms. [[Paper]](https://dl.acm.org/doi/10.1145/1031120.1031121)



+ 2004-IJCV - A Gibbs Point Process for Road Extraction from Remotely Sensed Images. [[Paper]](https://link.springer.com/article/10.1023/B:VISI.0000013086.45688.5d)



+ 2008-CVPR - Graph cut based image segmentation with connectivity priors. [[Paper]](https://ieeexplore.ieee.org/document/4587440)



+ 2008-CVIU - Topology cuts: A novel min-cut/max-flow algorithm for topology preserving segmentation in n–d images. [[Paper]](https://www.sciencedirect.com/science/article/pii/S1077314208001094)



+ 2009-CVPR - Global connectivity potentials for random field models. [[Paper]](https://ieeexplore.ieee.org/document/5206567)



+ 2010-ECCV - Learning to Detect Roads in High-Resolution Aerial Images. [[Paper]](https://www.cs.toronto.edu/~hinton/absps/road_detection.pdf)



+ 2011-ICCV -  Probabilistic image segmentation with closedness constraints. [[Paper]](https://ipa.iwr.uni-heidelberg.de/dokuwiki/Papers/andres2011probabilistic.pdf)



+ 2012-ICML - Learning to Label Aerial Images from Noisy Data. [[Paper]](https://www.cs.toronto.edu/~vmnih/docs/noisy_maps.pdf)



+ 2013-CVPR - A Higher-Order CRF Model for Road Network Extraction. [[Paper]](https://ieeexplore.ieee.org/document/6619066)



+ 2013-CVPR - Reconstructing Loopy Curvilinear Structures Using Integer Programming.[[Paper]](https://ieeexplore.ieee.org/document/6619082)



+ 2013-ICCV - Tree shape priors with connectivity constraints using convex relaxation on general graphs. [[Paper]](https://ieeexplore.ieee.org/document/6751401)



+ 2014-ECCV - Generalized connectivity constraints for spatio-temporal 3D reconstruction. [[Paper]](https://link.springer.com/chapter/10.1007/978-3-319-10593-2_3)



+ 2015-MIA - Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters. [[Paper]](https://www.sciencedirect.com/science/article/pii/S1361841514001455)



+ 2016-MICCAI - Topology Aware Fully Convolutional Networks For Histology Gland Segmentation. [[Paper]](http://www.sfu.ca/~abentaie/papers/miccai16.pdf)[[Code]](http://www.sfu.ca/~abentaie/topo_fcn/topo_fcn.html)



+ 2016-ISBI - Deep vessel tracking: A generalized probabilistic approach via deep learning. [[Paper]](https://www.sciencedirect.com/science/article/pii/026288569599723E)



+ 2016-TPAMI - Reconstructing curvilinear networks using path classifiers and integer programming. [[Paper]](https://ieeexplore.ieee.org/document/7405348)



+ 2017-ICCV - DeepRoadMapper: Extracting Road Topology From Aerial Images. [[Paper]](http://openaccess.thecvf.com/content_iccv_2017/html/Mattyus_DeepRoadMapper_Extracting_Road_ICCV_2017_paper.html)



+ 2017-ICCV - Efficient algorithms for moral lineage tracing. [[Paper]](https://arxiv.org/abs/1702.04111)



+ 2017-MICCAIW - Vascular segmentation in TOF MRA images of the brain using a deep convolutional neural network. [[Paper]](https://link.springer.com/chapter/10.1007/978-3-319-67534-3_5)



+ 2017- 3d convolutional neural networks with graph refinement for airway segmentation using incomplete data labels. [[Paper]](https://link.springer.com/chapter/10.1007/978-3-319-67389-9_17)



+ 2018-CVPR - Beyond the Pixel-Wise Loss for Topology-Aware Delineation. [[Paper]](https://arxiv.org/abs/1712.02190)



+ 2018-CVPR - Matching adversarial networks. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/html/Mattyus_Matching_Adversarial_Networks_CVPR_2018_paper.html)



+ 2018-CVPR - RoadTracer: Automatic Extraction of Road Networks From Aerial Images. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/html/Bastani_RoadTracer_Automatic_Extraction_CVPR_2018_paper.html)[[Code]](https://github.com/mitroadmaps/roadtracer)[[Project Page]](https://roadmaps.csail.mit.edu/roadtracer/)



+ 2018-CVPRW - D-LinkNet: LinkNet With Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Zhou_D-LinkNet_LinkNet_With_CVPR_2018_paper.html)[[Code]](https://github.com/zlkanata/DeepGlobe-Road-Extraction-Challenge)



+ 2018-CVPRW - D-LinkNet: LinkNet With Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Zhou_D-LinkNet_LinkNet_With_CVPR_2018_paper.html)



+ 2018-CVPRW - Stacked U-Nets With Multi-Output for Road Extraction. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Sun_Stacked_U-Nets_With_CVPR_2018_paper.html)



+ 2018-CVPRW - Fully Convolutional Network for Automatic Road Extraction From Satellite Imagery. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Buslaev_Fully_Convolutional_Network_CVPR_2018_paper.html)



+ 2018-CVPRW - Road Detection With EOSResUNet and Post Vectorizing Algorithm. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Filin_Road_Detection_With_CVPR_2018_paper.html)



+ 2018-BMVC - Iterative Deep Learning for Road Topology Extraction. [[Paper]](https://arxiv.org/abs/1808.09814)



+ 2018-MICCAI - A multi-task network to detect junctions in retinal vasculature. [[Paper]](https://arxiv.org/abs/1806.03175)



+ 2018-NeuroComp - Retinal vessel segmentation of color fundus images using multiscale convolutional neural network with an improved cross-entropy loss function. [[Paper]](https://www.sciencedirect.com/science/article/pii/S0925231218305423)



+ 2018-SReports - Whole-brain vasculature reconstruction at the single capillary level. [[Paper]](https://www.nature.com/articles/s41598-018-30533-3)



+ 2018-Arxiv -  Deepvesselnet: Vessel segmentation, centerline prediction, and bifurcation detection in 3-d angiographic volumes. [[Paper]](https://arxiv.org/abs/1803.09340)



+ 2019-CVPR - Leveraging Crowdsourced GPS Data for Road Extraction From Aerial Imagery. [[Paper]](http://openaccess.thecvf.com/content_CVPR_2019/html/Sun_Leveraging_Crowdsourced_GPS_Data_for_Road_Extraction_From_Aerial_Imagery_CVPR_2019_paper.html)[[Code]](https://github.com/suniique/Leveraging-Crowdsourced-GPS-Data-for-Road-Extraction-from-Aerial-Imagery)



+ 2019-CVPR - Improved Road Connectivity by Joint Learning of Orientation and Segmentation. [[Paper]](http://openaccess.thecvf.com/content_CVPR_2019/html/Batra_Improved_Road_Connectivity_by_Joint_Learning_of_Orientation_and_Segmentation_CVPR_2019_paper.html)[[Code]](https://github.com/anilbatra2185/road_connectivity)



+ 2019-ICCV - Neural Turtle Graphics for Modeling City Road Layouts. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2019/html/Chu_Neural_Turtle_Graphics_for_Modeling_City_Road_Layouts_ICCV_2019_paper.html)[[Project Page]](https://amlankar.github.io/publication/ntg/)



+ 2019-ICCV - Recurrent U-Net for Resource-Constrained Segmentation. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2019/html/Wang_Recurrent_U-Net_for_Resource-Constrained_Segmentation_ICCV_2019_paper.html)



+ 2019-ICCV - Topological map extraction from overhead images. [[Paper]](http://openaccess.thecvf.com/content_ICCV_2019/html/Li_Topological_Map_Extraction_From_Overhead_Images_ICCV_2019_paper.html)



+ 2019-NIPS - Topology-Preserving Deep Image Segmentation. [[Paper]](https://papers.nips.cc/paper/8803-topology-preserving-deep-image-segmentation.pdf)[[Code1]](https://github.com/HuXiaoling/TopoLoss)[[Code2]](https://github.com/HuXiaoling/imageSeg-2.5D_topo)



+ 2019-MICCAI - A deep learning design for improving topology coherence in blood vessel segmentation. [[Paper]](https://link.springer.com/chapter/10.1007/978-3-030-32239-7_11)[[Code]](https://github.com/rjtaraujo/dvae-refiner)



+ 2019-MLMI - Shape-aware complementary-task learning for multi-organ segmentation. [[Paper]](https://arxiv.org/abs/1908.05099)



+ 2019-TGRS - Road Detection and Centerline Extraction Via Deep Recurrent Convolutional Neural Network U-Net. [[Paper]](https://ieeexplore.ieee.org/document/8714072)



+ 2019-TPAMI - Joint Segmentation and Path Classication of Curvilinear Structures. [[Paper]](https://arxiv.org/abs/1905.03892)



+ 2019-TPAMI - Large scale image segmentation with structured loss based deep learning for connectome reconstruction. [[Paper]](https://ieeexplore.ieee.org/document/8364622)



+ 2019-Arxiv -  Image-conditioned graph generation for road network extraction. [[Paper]](https://arxiv.org/abs/1910.14388)[[Code]](https://github.com/davide-belli/generative-graph-transformer)



+ 2019-biorxiv - Automated analysis of whole brain vasculature using machine learning. [[Paper]](https://www.biorxiv.org/content/10.1101/613257v1)



+ 2020-WACV - Reconstructing Road Network Graphs from both Aerial Lidar and Images. [[Paper]](http://openaccess.thecvf.com/content_WACV_2020/html/Parajuli_Reconstructing_Road_Network_Graphs_from_both_Aerial_Lidar_and_Images_WACV_2020_paper.html)



+ 2020-WACV - City-Scale Road Extraction from Satellite Imagery v2: Road Speeds and Travel Times. [[Paper]](http://openaccess.thecvf.com/content_WACV_2020/html/Van_Etten_City-Scale_Road_Extraction_from_Satellite_Imagery_v2_Road_Speeds_and_WACV_2020_paper.html)



+ 2020-CVPR - VecRoad: Point-Based Iterative Graph Exploration for Road Graphs Extraction. [[Paper]](http://mftp.mmcheng.net/Papers/20CvprVecRoad.pdf)[[Project Page]](https://mmcheng.net/vecroad/)



+ 2020-ECCV - TopoGAN: A Topology-Aware Generative Adversarial Network. [[Paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480120.pdf)[[Supple]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480120-supp.pdf)



+ 2020-ECCV - TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation. [[Paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720222.pdf)



+ 2020-MICCAI - A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images. [[Paper]](https://arxiv.org/abs/2007.05324)



+ 2020-TPAMI - A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology. [[Paper]](https://arxiv.org/abs/1910.01877)



+ 2020-CMIG - Learning tree-structured representation for 3d coronary artery segmentation. [[Paper]](https://www.sciencedirect.com/science/article/pii/S089561111930103X)



+ 2020-Arxiv - Promoting Connectivity of Network-Like Structures by Enforcing Region Separation. [[Paper]](https://arxiv.org/pdf/2009.07011.pdf)



+ 2020-Arxiv - clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation. [[Paper]](https://arxiv.org/pdf/2003.07311.pdf)[[Code]](https://github.com/cpuimage/clDice)



**Datasets**



+ 2018 - SpaceNet: A Remote Sensing Dataset and Challenge Series. [[Paper]](https://arxiv.org/abs/1807.01232)[[Dataset]](https://spacenetchallenge.github.io/datasets/datasetHomePage.html)



+ 2018-CVPRW - DeepGlobe 2018: A Challenge to Parse the Earth Through Satellite Images. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018_workshops/w4/html/Demir_DeepGlobe_2018_A_CVPR_2018_paper.html)[[Project Page]](http://deepglobe.org/)



+ 2018-CVPR - RoadTracer: Automatic Extraction of Road Networks From Aerial Images. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/html/Bastani_RoadTracer_Automatic_Extraction_CVPR_2018_paper.html)[[Dataset]](https://github.com/mitroadmaps/roadtracer)[[Project Page]](https://roadmaps.csail.mit.edu/roadtracer/)



**Metrics**

+ 1998 - CCQ:- Empirical Evaluation of Automatically Extracted Road Axes.[[Paper]](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.5701)



+ 2012 - Holes and Marbles:- Inferring road maps from global positioning system traces: Survey and comparative evaluation. [[Paper]](https://www.cs.uic.edu/~jakob/papers/biagioni-trr12.pdf)



+ 2013-CVPR - TLTS:- A Higher-Order CRF Model for Road Network Extraction. [[Paper]](https://ieeexplore.ieee.org/document/6619066)



+ 2018 - APLS:- SpaceNet: A Remote Sensing Dataset and Challenge Series. [[Paper]](https://arxiv.org/abs/1807.01232)



+ 2018-CVPR - Junctin Score:- RoadTracer: Automatic Extraction of Road Networks From Aerial Images. [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/html/Bastani_RoadTracer_Automatic_Extraction_CVPR_2018_paper.html)



+ 2020-ECCV - Towards Reliable Evaluation of Road Network Reconstructions. [[Paper]](http://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6424_ECCV_2020_paper.php)



**Textbooks**



+ [Combinatorial Topology by Pavel S Aleksandrov](https://books.google.ch/books/about/Combinatorial_Topology.html?id=pZ3HcV9cPOAC&redir_esc=y)



+ [Computational topology: an introduction by Herbert Edelsbrunner](https://www.maths.ed.ac.uk/~v1ranick/papers/edelcomp.pdf)



+ [Machine Learning for Aerial Image Labeling, PhD Thesis](https://www.cs.toronto.edu/~vmnih/docs/Mnih_Volodymyr_PhD_Thesis.pdf)



+ [Digital Topology by Ulrich Eckhardt](https://www.math.uni-hamburg.de/home/eckhardt/P124_941.pdf)



+ [Digital topology by Azriel Rosenfeld](https://www.tandfonline.com/doi/abs/10.1080/00029890.1979.11994873)