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论文笔记-Multimodal Unsupervised Image-to-Image Translation

论文信息论文标题:Multimodal Unsupervised Image-to-Image Translation论文出处:ECCV 2018论文作者:Xun Huang, Ming-Yu Liu, Serge J. Belongie, Jan Kautz研究机构:康奈尔大学;英伟达代码链接:https://github.com/nvlabs/MUNIT引用信息:@inproceedings{DBLP:conf/eccv/HuangLBK18, autho

2020-10-02 23:53:37

论文笔记-Unsupervised Domain Adaptation via Regularized Conditional Alignment

论文信息论文标题:Unsupervised Domain Adaptation via Regularized Conditional Alignment论文作者:Safa Cicek, Stefano Soatto研究机构:UCLA Vision Lab; University of California, Los Angeles论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/CicekS19, author =

2020-09-28 23:24:16

论文笔记-Semi-Supervised Learning by Augmented Distribution Alignment

论文信息论文标题:Semi-Supervised Learning by Augmented Distribution Alignment论文作者:Qin Wang, Wen Li, Luc Van Gool研究机构:ETH Zurich; KU Leuven论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/WangLG19, author = {Qin Wang and Wen Li a

2020-09-27 20:35:30

论文笔记-Domain Adaptation for Semantic Segmentation with Maximum Squares Loss

论文信息论文标题:Domain Adaptation for Semantic Segmentation with Maximum Squares Loss论文作者:Minghao Chen, Hongyang Xue, Deng Cai研究机构:浙江大学;阿里巴巴—浙江大学前沿技术联合研究中心论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/0001XC19, author = {Minghao Chen and

2020-09-26 23:07:03

论文笔记-Domain Adaptation for Structured Output via Discriminative Patch Representations

论文信息论文标题:Domain Adaptation for Structured Output via Discriminative Patch Representations论文作者: Yi-Hsuan Tsai, Kihyuk Sohn, Samuel Schulter, Manmohan Chandraker研究机构:NEC 实验室;CMU论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/TsaiSSC19, aut

2020-09-25 22:55:41

论文笔记-Self-Supervised Monocular Depth Hints

论文信息论文标题:Self-Supervised Monocular Depth Hints论文作者:Jamie Watson, Michael Firman, Gabriel J. Brostow, Daniyar Turmukhambetov研究机构:Niantic; UCL论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/WatsonFBT19, author = {Jamie Watson and

2020-09-23 18:46:31

论文笔记-SSF-DAN: Separated Semantic Feature based Domain Adaptation Network for Semantic Segmentation

论文信息论文标题:SSF-DAN: Separated Semantic Feature based Domain Adaptation Network for Semantic Segmentation论文作者: Liang Du, Jingang Tan, Hongye Yang, Jianfeng Feng, Xiangyang Xue, Qibao Zheng, Xiaoqing Ye, Xiaolin Zhang研究机构:中科院上海为系统信息技术所;复旦大学;百度;上海科技大学

2020-09-22 23:12:26

论文笔记-All about Structure - Adapting Structural Information across Domains for Boosting Semantic Segm

论文信息论文标题:All about Structure - Adapting Structural Information across Domains for Boosting Semantic Segmentation论文作者:Wei-Lun Chang, Hui-Po Wang, Wen-Hsiao Peng, Wei-Chen Chiu研究机构:台湾交通大学论文出处:CVPR 2019引用信息:@inproceedings{DBLP:conf/cvpr/ChangW

2020-09-21 22:46:12

论文笔记-Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation

论文信息论文标题:Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation论文作者:Seungmin Lee, Dongwan Kim, Namil Kim, Seong-Gyun Jeong研究机构:首尔国立大学,NAVER LABS, CODE42.ai论文出处:ICCV 2019引用信息:@inproceedings{DBLP:conf/iccv/LeeKKJ19

2020-09-20 22:22:53

论文笔记-Transformation GAN for Unsupervised Image Synthesis and Representation Learning

论文信息论文标题:Transformation GAN for Unsupervised Image Synthesis and Representation Learning论文作者:Jiayu Wang, Wengang Zhou, Guo-Jun Qi, Zhongqian Fu, Qi Tian, Houqiang Li研究机构:中国科学技术大学;Futurewei论文出处:CVPR 2020引用信息:@inproceedings{DBLP:conf/cvpr/Wan

2020-09-19 00:32:46

论文笔记-AdderNet: Do We Really Need Multiplications in Deep Learning?

论文信息论文标题:AdderNet: Do We Really Need Multiplications in Deep Learning?论文作者:Hanting Chen, Yunhe Wang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu研究机构:北京大学、华为诺亚实验室、悉尼大学论文出处:CVPR 2020引用信息:@inproceedings{DBLP:conf/cvpr/ChenWXSX0X20, au

2020-09-14 23:22:19

论文笔记-StereoGAN: Bridging S2R Domain Gap by Joint Optimization Domain Translation and Stereo Matching

论文信息论文标题:StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching论文作者:Rui Liu, Chengxi Yang, Wenxiu Sun, Xiaogang Wang, Hongsheng Li研究机构:商汤,香港中文大学论文出处:CVPR 2020引用信息:@inproceedings{DBLP

2020-09-13 20:52:25

论文笔记-Domain Decluttering Simplifying Images to Mitigate Synthetic-Real Domain Shift...

论文信息论文标题:Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation论文作者:Yunhan Zhao, Shu Kong, Daeyun Shin, Charless Fowlkes研究机构:UC Irvine; Carnegie Mellon University论文出处:CVPR 2020引用信息:@inpr

2020-09-12 23:56:58

论文笔记-SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

论文信息论文标题:SharinGAN - Combining Synthetic and Real Data for Unsupervised Geometry Estimation论文作者:Koutilya PNVR, Hao Zhou, David Jacobs研究机构:University of Maryland, College Park, MD, USA.论文出处:CVPR 2020引用信息:@inproceedings{DBLP:conf/cvpr/PNVRZJ2

2020-09-11 23:49:41

论文笔记-Learning to Adapt Structured Output Space for Semantic Segmentation

论文信息论文标题:Learning to Adapt Structured Output Space for Semantic Segmentation论文作者:Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, Manmohan Chandraker研究机构:NEC Laboratories America; University of California, Merced; Unive

2020-09-10 08:03:06

论文笔记-Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid(待校正)

论文信息论文标题:Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid论文作者:Jun Gao, Zian Wang, Jinchen Xuan, Sanja Fidler研究机构:University of Toronto, Vector Institute, NVIDIA, Peking University论文出处:ECCV 2020引用信息:@articl

2020-09-08 11:26:32

论文笔记-Unsupervised Domain Adaptation with Dual-Scheme Fusion Network for Medical Image Segmentation

论文信息论文标题:Unsupervised Domain Adaptation with Dual-Scheme Fusion Network for Medical Image Segmentation论文作者:Danbing Zou, Qikui Zhu, Pingkun Yan研究机构:武汉大学,Department of Biomedical Engineering, Troy, NY, USA论文出处:IJCAI 2020引用信息:@inproceedings{DB

2020-09-07 11:08:58

论文笔记-DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

论文信息论文标题:DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency论文作者:Yuliang Zou, Zelun Luo, Jia-Bin Huang研究机构:Virginia Tech; Stanford University论文出处:ECCV 2018引用信息:@inproceedings{DBLP:conf/eccv/ZouLH18, author

2020-09-06 17:15:31

论文笔记-Monocular Depth Estimation Using Whole Strip Masking and Reliability-Based Refinement

论文信息论文标题:Monocular Depth Estimation Using Whole Strip Masking and Reliability-Based Refinement论文作者:Minhyeok Heo, Jaehan Lee, Kyung-Rae Kim, Han-Ul Kim, Chang-Su Kim研究机构:NAVER LABS;论文出处:School of Electrical Engineering, Korea University引用信息:

2020-09-05 10:35:21

论文笔记-Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation

论文信息论文标题:Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation论文作者:Zhenyu Zhang, Zhen Cui, Chunyan Xu, Zequn Jie, Xiang Li, Jian Yang研究机构:Nanjing University of Science and Technology;Tencent AI Lab论文出处:ECCV 2018引用信息:@

2020-09-04 21:03:55

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