正在加载图片...
第4期 董俊杰,等:基于反馈注意力机制和上下文融合的非模式实例分割 ·809· 15-04-10)[2020-07-21]https:/axiv.org/abs/1409.1556 tchable atrous convolution[EB/OL].(2020-06-03)[2020- [2]HE Kaiming,ZHANG Xiangyu,REN Shaoging,et al. 07-21]https://arxiv.org/abs/2006.02334 Deep residual learning for image recognition[C]//Pro- [14]LI Yi,QI Haozhi,DAI Jifeng,et al.Fully convolutional ceedings of 2016 IEEE Conference on Computer Vision instance-aware semantic segmentation[C]//Proceedings of and Pattern Recognition(CVPR).Las Vegas,NV,USA, 2017 IEEE Conference on Computer Vision and Pattern 2016:770-778. Recognition.Honolulu,United States,2017:4438-4446. [3]LIU Wei,ANGUELOV D,ERHAN D,et al.SSD:single [15]LIU Shu,QI Lu,QIN Haifang,et al.Path aggregation net- shot MultiBox detector[Cl//Proceedings of the 14th Euro- work for instance segmentation[C]//Proceedings of 2018 pean Conference on Computer Vision.Amsterdam,The IEEE/CVF Conference on Computer Vision and Pattern Netherlands,2016:21-37 Recognition.Salt Lake City,United States,2018: [4]REN Shaoqing,HE Kaiming,GIRSHICK R,et al.Faster 8759-8768. R-CNN:towards real-time object detection with region [16]CHEN Xinlei,GIRSHICK R,HE Kaiming,et al proposal networks[J].IEEE transactions on pattern analys- Tensormask:a foundation for dense object segmenta- is and machine intelligence,2017,39(6):1137-1149. tion[C]//Proceedings of 2019 IEEE/CVF International [5]LIN T Y,GOYAL P,GIRSHICK R,et al.Focal loss for Conference on Computer Vision.Seoul,South Korea, dense object detection[Cl//Proceedings of 2017 IEEE In- 2019:2061-2069. ternational Conference on Computer Vision.Venice,Italy, [17]XIE Enze,SUN Peize,SONG Xiaoge,et al.PolarMask: 2017:2999-3007 single shot instance segmentation with polar representa- [6]GIRSHICK R.Fast R-CNNICV//Proceedings of 2015 IEEE tion[C]//Proceedings of the IEEE/CVF Conference on International Conference on Computer Vision(ICCV). Computer Vision and Pattern Recognition.Seattle,United Santiago,Chile,2015:1440-1448 States,2020:12190-12199. [7]LONG J,SHELHAMER E,DARRELL T.Fully convolu- [18]LI Ke,MALIK J.Amodal instance segmentation[C]//Pro- tional networks for semantic segmentation[C]//Pr-oceed- ceedings of the 14th European Conference on Computer ings of 2015 IEEE Conference on Computer Vision and Vision.Amsterdam,The Netherlands,2016:677-693. Pattern Recognition.Boston,America,2015:3431-3440. [19]FOLLMANN P,KONIG R,HARTINGER P,et al. [8]CHEN L C,PAPANDREOU G,SCHROFF F,et al.Re- Learning to see the invisible:end-to-end trainable amodal thinking atrous convolution for semantic image segme-nt- instance segmentation[C]//2019 IEEE Winter Conference ation[EB/OL].(2017-10-05)[2020-07-21]https://arxiv.org/ on Applications of Computer Vision (WACV).Waikoloa, abs/1706.05587 United States,2019:1328-1336 [9]HE Kaiming,GKIOXARI G,DOLLAR P,et al.Mask R- [20]EHSANI K,MOTTAGHI R,FARHADI A.SeGAN:seg- CNN[C]//Proceedings of 2017 IEEE International Confer- menting and generating the invisible[C]//Proceedings of ence on Computer Vision.Venice,Italy,2017:2980-2988. 2018 IEEE/CVF Conference on Computer Vision and [10]BOLYA D,ZHOU Chong,XIAO Fanyi,et al.YOLACT: Pattern Recognition.Salt Lake City,United States,2018: real-time instance segmentation[Cl/Proceedings of 2019 6144-6153. IEEE/CVF International Conference on Computer Vision. [21]HU Jie,SHEN Li,SUN Gang.Squeeze-and-excitation Seoul,South Korea,2019:9156-9165. networks[Cl//Proceedings of 2018 IEEE/CVF Confer- [11]ZHU Yan,TIAN Yuandong,METAXAS D,et al.Se- ence on Computer Vision and Pattern Recognition.Salt mantic amodal segmentation[Cl//Proceedings of the 30th Lake City,United States,2018:7132-7141. IEEE Conference on Computer Vision and Pattern Recog- [22]WANG Xiaolong,GIRSHICK R,GUPTA A,et al.Non- nition.Honolulu.United States,2017:3001-3009 local neural networks[C]//Proceedings of 2018 IEEE/CVF [12]ZHANG Ziheng,CHEN Aapei,XIE Ling,et al.Learning Conference on Computer Vision and Pattern Recognition semantics-aware distance map with semantics layering Salt Lake City,United States,2018:7794-7803 network for amodal instance segmentation[C]//Pro-ceed- [23]WOO S,PARK J,LEE J Y,et al.CBAM:convolutional ings of the 27th ACM International Conference on Multi- block attention module[C]//Proceedings of the 15th Euro- media.Nice,France,2019:2124-2132 pean Conference on Computer Vision (ECCV).Munich, [13]QIAO Siyuan,CHEN L C,YUILLE A.DetectoRS:de- Germany,.2018:3-19. tecting objects with recursive feature pyramid and swi- [24]CAO Yun,XU Jiarui,LIN S,et al.GCNet:non-local net-15-04-10)[2020-07-21] https://arxiv.org/abs/1409.1556. HE Kaiming, ZHANG Xiangyu, REN Shaoqing, et al. Deep residual learning for image recognition[C]//Pro￾ceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA, 2016: 770−778. [2] LIU Wei, ANGUELOV D, ERHAN D, et al. SSD: single shot MultiBox detector[C]//Proceedings of the 14th Euro￾pean Conference on Computer Vision. Amsterdam, The Netherlands, 2016: 21−37. [3] REN Shaoqing, HE Kaiming, GIRSHICK R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE transactions on pattern analys￾is and machine intelligence, 2017, 39(6): 1137–1149. [4] LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[C]//Proceedings of 2017 IEEE In￾ternational Conference on Computer Vision. Venice, Italy, 2017: 2999−3007. [5] GIRSHICK R. Fast R-CNN[C]//Proceedings of 2015 IEEE International Conference on Computer Vision (ICCV). Santiago, Chile, 2015: 1440−1448. [6] LONG J, SHELHAMER E, DARRELL T. Fully convolu￾tional networks for semantic segmentation[C]//Pr- oceed￾ings of 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, America, 2015: 3431−3440. [7] CHEN L C, PAPANDREOU G, SCHROFF F, et al. Re￾thinking atrous convolution for semantic image segme- nt￾ation[EB/OL]. (2017-10-05)[2020-07-21] https://arxiv.org/ abs/1706.05587. [8] HE Kaiming, GKIOXARI G, DOLLÁR P, et al. Mask R￾CNN[C]//Proceedings of 2017 IEEE International Confer￾ence on Computer Vision. Venice, Italy, 2017: 2980−2988. [9] BOLYA D, ZHOU Chong, XIAO Fanyi, et al. YOLACT: real-time instance segmentation[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision. Seoul, South Korea, 2019: 9156−9165. [10] ZHU Yan, TIAN Yuandong, METAXAS D, et al. Se￾mantic amodal segmentation[C]//Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recog￾nition. Honolulu, United States, 2017: 3001−3009. [11] ZHANG Ziheng, CHEN Aapei, XIE Ling, et al. Learning semantics-aware distance map with semantics layering network for amodal instance segmentation[C]//Pro- ceed￾ings of the 27th ACM International Conference on Multi￾media. Nice, France, 2019: 2124−2132. [12] QIAO Siyuan, CHEN L C, YUILLE A. DetectoRS: de￾tecting objects with recursive feature pyramid and swi- [13] tchable atrous convolution[EB/OL]. (2020-06-03)[2020- 07- 21] https://arxiv.org/abs/2006.02334. LI Yi, QI Haozhi, DAI Jifeng, et al. Fully convolutional instance-aware semantic segmentation[C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, United States, 2017: 4438−4446. [14] LIU Shu, QI Lu, QIN Haifang, et al. Path aggregation net￾work for instance segmentation[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, United States, 2018: 8759−8768. [15] CHEN Xinlei, GIRSHICK R, HE Kaiming, et al. Tensormask: a foundation for dense object segmenta￾tion[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision. Seoul, South Korea, 2019: 2061−2069. [16] XIE Enze, SUN Peize, SONG Xiaoge, et al. PolarMask: single shot instance segmentation with polar representa￾tion[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, United States, 2020: 12190−12199. [17] LI Ke, MALIK J. Amodal instance segmentation[C]//Pro￾ceedings of the 14th European Conference on Computer Vision. Amsterdam, The Netherlands, 2016: 677−693. [18] FOLLMANN P, KÖNIG R, HÄRTINGER P, et al. Learning to see the invisible: end-to-end trainable amodal instance segmentation[C]//2019 IEEE Winter Conference on Applications of Computer Vision (WACV). Waikoloa, United States, 2019: 1328−1336. [19] EHSANI K, MOTTAGHI R, FARHADI A. SeGAN: seg￾menting and generating the invisible[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, United States, 2018: 6144−6153. [20] HU Jie, SHEN Li, SUN Gang. Squeeze-and-excitation networks[C]//Proceedings of 2018 IEEE/CVF Confer￾ence on Computer Vision and Pattern Recognition. Salt Lake City, United States, 2018: 7132−7141. [21] WANG Xiaolong, GIRSHICK R, GUPTA A, et al. Non￾local neural networks[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, United States, 2018: 7794−7803. [22] WOO S, PARK J, LEE J Y, et al. CBAM: convolutional block attention module[C]//Proceedings of the 15th Euro￾pean Conference on Computer Vision (ECCV). Munich, Germany, 2018: 3−19. [23] [24] CAO Yun, XU Jiarui, LIN S, et al. GCNet: non-local net- 第 4 期 董俊杰,等:基于反馈注意力机制和上下文融合的非模式实例分割 ·809·
<<向上翻页向下翻页>>
©2008-现在 cucdc.com 高等教育资讯网 版权所有