Flickr1024
No Label
Super Resolution
|...
许可协议: Custom

Overview

Flickr1024 is a large-scale stereo image dataset which consists of 1024 high-quality image pairs and covers diverse senarios. Details of this dataset can be found in our published paper. Although the Flickr1024 dataset was originally developed for stereo image SR (click here for an overview), it was also used for many other tasks such as reference-based SR, stereo matching, and stereo image denoising.

Image Sample

img

Citation

  @InProceedings{Flickr1024,
  author    = {Wang, Yingqian and Wang, Longguang and Yang, Jungang and An, Wei and Guo, Yulan},
  title     = {Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution},
  booktitle = {International Conference on Computer Vision Workshops},
  pages     = {3852-3857},
  month     = {Oct},
  year      = {2019}
  }

  @Article{PAM,
  author  = {Wang, Longguang and Guo, Yulan and Wang, Yingqian and Liang, Zhengfa and Lin,
Zaiping and Yang, Jungang and An, Wei},
  title   = {Parallax Attention for Unsupervised Stereo Correspondence Learning},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year    = {2020},
  }

  @inproceedings{PASSRnet,
  title     = {Learning parallax attention for stereo image super-resolution},
  author    = {Wang, Longguang and Wang, Yingqian
and Liang, Zhengfa and Lin, Zaiping and Yang, Jungang and An, Wei and Guo, Yulan},
  booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages     = {12250--12259},
  year      = {2019}
  }

License

Custom

数据概要
数据格式
Image,
数据量
--
文件大小
2.36GB
发布方
Yingqian Wang
Yingqian Wang is a Ph.D. StudentNational University of Defense Technology (NUDT)
数据集反馈
| 195 | 数据量 -- | 大小 2.36GB
Flickr1024
No Label
Super Resolution
许可协议: Custom

Overview

Flickr1024 is a large-scale stereo image dataset which consists of 1024 high-quality image pairs and covers diverse senarios. Details of this dataset can be found in our published paper. Although the Flickr1024 dataset was originally developed for stereo image SR (click here for an overview), it was also used for many other tasks such as reference-based SR, stereo matching, and stereo image denoising.

Image Sample

img

Citation

  @InProceedings{Flickr1024,
  author    = {Wang, Yingqian and Wang, Longguang and Yang, Jungang and An, Wei and Guo, Yulan},
  title     = {Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution},
  booktitle = {International Conference on Computer Vision Workshops},
  pages     = {3852-3857},
  month     = {Oct},
  year      = {2019}
  }

  @Article{PAM,
  author  = {Wang, Longguang and Guo, Yulan and Wang, Yingqian and Liang, Zhengfa and Lin,
Zaiping and Yang, Jungang and An, Wei},
  title   = {Parallax Attention for Unsupervised Stereo Correspondence Learning},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year    = {2020},
  }

  @inproceedings{PASSRnet,
  title     = {Learning parallax attention for stereo image super-resolution},
  author    = {Wang, Longguang and Wang, Yingqian
and Liang, Zhengfa and Lin, Zaiping and Yang, Jungang and An, Wei and Guo, Yulan},
  booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages     = {12250--12259},
  year      = {2019}
  }

License

Custom

数据集反馈
0
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