光场数据库mark

https://blog.csdn.net/hoyjam1/article/details/77968883

http://hci-lightfield.iwr.uni-heidelberg.de/

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Welcome to the 4D Light Field Benchmark website. This website provides light field data, software tools, and a benchmark evaluation as described in the ACCV 2016 paper "A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields".

Per scene, we provide:

• 9x9x512x512x3 light fields as individual PNGs
• Config files with camera settings and disparity ranges
• Per center view (except for the 4 test scenes):
  • 512x512 and 5120x5120 depth and disparity maps as PFMs
  • 512x512 and 5120x5120 evaluation masks as PNGs

We further provide depth and disparity maps for all 81 views of the additional scenes.
For file format descriptions and read/write utilities, see our Matlab and Python scripts.

根据场景，我们提供：
9x9x512x512x3光场作为单独的PNG
使用相机设置和视差范围配置文件
每个中心视图（4个测试场景除外）：
512x512和5120x5120深度和视差图作为PFM
512x512和5120x5120评估掩码作为PNG
我们还为所有81个视图提供了深度和视差图。
有关文件格式描述和读/写实用程序，请参阅我们的Matlab和Python脚本。

http://mmspg.epfl.ch/EPFL-light-field-image-dataset

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You can download all image files (LFR, thumbanails, depthmaps, and camera calibration data) from the following FTP (please use dedicated FTP clients, such as FileZilla or FireFTP):

 

FTP address: ftp://tremplin.epfl.ch

User name: [email protected]

Password: 48HMd6tm4SxC6s3z

 

The total size of the dataset is about  55 GB.

If you use this dataset in your research, we kindly ask you to reference the following paper and URL link of this website:

 

M. Řeřábek and T. Ebrahimi, "New Light Field Image Dataset," 8th International Conference on Quality of Multimedia Experience (QoMEX), Lisbon, Portugal, 2016

 

URL link:  http://mmspg.epfl.ch/EPFL-light-field-image-dataset

 

You may also check the above paper for some other helpful information.

 

In case of any problems or questions, please send an email to martin.rerabek (at) epfl.ch

 

Copyright

Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute the data provided and its documentation for research purpose only. The data provided may not be commercially distributed. In no event shall the Ecole Polytechnique Fédérale de Lausanne (EPFL) be liable to any party for direct, indirect, special, incidental, or consequential damages arising out of the use of the data and its documentation. The Ecole Polytechnique Fédérale de Lausanne (EPFL) specifically disclaims any warranties. The data provided hereunder is on an "as is" basis and the Ecole Polytechnique Fédérale de Lausanne (EPFL) has no obligation to provide maintenance, support, updates, enhancements, or modifications.

http://www.cvlibs.net/projects/autonomous_vision_survey/

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