图像分割二十年,盘点影响力最大的10篇论文
AI算法与图像处理
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2020-10-02 14:26
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导读
图像分割(image segmentation)技术是计算机视觉领域的重要的研究方向,近些年,图像分割技术迅猛发展,在多个视觉研究领域都有着广泛的应用。本文盘点了近20年来影响力最大的 10 篇论文。
发布信息: 2017,16th IEEE International Conference on Computer Vision (ICCV)
论文:https://arxiv.org/abs/1703.06870
代码:https://github.com/facebookresearch/Detectron
![](https://filescdn.proginn.com/15cd0a78868057309ee57d198711b2e7/8da5d235b92982c9d3318e8026362274.webp)
![](https://filescdn.proginn.com/ebe3e2d7104a54b91198d683fb90c33c/7166d12f83579e81b4ff2a46aef6b8fc.webp)
发布信息:2015,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
论文:https://arxiv.org/pdf/1511.00561.pdf
代码:https://github.com/aizawan/segnet
![](https://filescdn.proginn.com/4ebff2a72e500fcecb6c954aca3ef65b/5d6e239017c0dbcadc74fe51abf25865.webp)
![](https://filescdn.proginn.com/7b9950299a0edf89b2d1d58b11a1aec5/80664130f074fe1ea21e13870339c1aa.webp)
发布信息:2018,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
DeepLabv2:https://arxiv.org/pdf/1606.00915.pdf
DeepLabv3:https://arxiv.org/pdf/1706.05587.pdf
DeepLabv3+:https://arxiv.org/pdf/1802.02611.pdf
代码:https://github.com/tensorflow/models/tree/master/research/deeplab
![](https://filescdn.proginn.com/4b9e9cc5ca43aac1c739ec5d1e87a908/0804109d34f1646056f66fa0d99b1318.webp)
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发布信息:2011,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
论文和代码:https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html
![](https://filescdn.proginn.com/57ac9ab6d9ba06382159e62985ca2016/97047c555fb87ba0e1fd7667c125e2ba.webp)
发布信息:2004,INTERNATIONAL JOURNAL OF COMPUTER VISION
论文和代码:http://cs.brown.edu/people/pfelzens/segment/
![](https://filescdn.proginn.com/9bcaf9d3deb922e3b46206db256d7e3e/2b20af4b22f9804d5f8230b8f9eaec3a.webp)
发布信息:2012,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
论文和代码:https://ivrlwww.epfl.ch/supplementary_material/RK_SLICSuperpixels/index.html
![](https://filescdn.proginn.com/ffaf4675b5b0cc634ad984fc2fccbe16/e0c0e33847f77ee7a4e2595de78007a2.webp)
发布信息:2015,18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
代码:https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/
![](https://filescdn.proginn.com/f3afffe47ac0c730a0d85f6bef3cc3d3/09a25c3349e46dc52d827dceeadb094a.webp)
发布信息:2002,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
发布信息:2000,IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 论文:https://ieeexplore.ieee.org/abstract/document/1000236
![](https://filescdn.proginn.com/710a6aa966b832ea08a97b173c2ae533/07737ffd4055ab4efb6134f39276d5d1.webp)
发布信息:2015,IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
代码:https://github.com/shelhamer/fcn.berkeleyvision.org
(2)增大数据尺寸的反卷积(deconv)层。能够输出精细的结果。
(3)结合不同深度层结果的跳级(skip)结构。同时确保鲁棒性和精确性。
![](https://filescdn.proginn.com/792dbafa57634410707efeeba1c2b93e/8974d87fc9dc97fd7765c2f56764eb8b.webp)
[1]FCN的学习及理解(Fully Convolutional Networks for Semantic Segmentation),CSDN
[2]mean shift 图像分割 (一),CSDN
[3]https://zhuanlan.zhihu.com/p/49512872
[4]图像分割—基于图的图像分割(Graph-Based Image Segmentation),CSDN
[5]https://www.cnblogs.com/fourmi/p/9785377.html
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