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download_lamem.tar.gz

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+oid sha256:948d7b634101d8f5afcf0e3d0c9a01ed973c4e96c8a40c52350a02fa64083524
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lamem/LICENSE

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+ Terms of use: by downloading the image data (LaMem), you agree to the following terms:
+  1.  You will use the data only for non-commercial research and educational purposes.
+  2.  You will NOT distribute the above images.
+  3.  MIT makes no representations or warranties regarding the data, including but not limited to warranties of non-infringement or fitness for a particular purpose.
+  4.  You accept full responsibility for your use of the data and shall defend and indemnify MIT, including their employees, officers and agents, against any and all claims arising from your use of the data, including but not limited to your use of any copies of copyrighted images that you may create from the data.
+
+Copyright (c) 2015 Aditya Khosla

lamem/README

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+LaMem: A Large-Scale Dataset for Image Memorability
+
+In this package, we include the images and their memorability scores, after accounting
+for false alarms. The images are available in the 'images/' folder and the memorability
+scores  are available in the 'splits/' folder. In the splits folder, we provide information 
+for 5 splits of the data, each consisting of the train, val and test sets (e.g., train_1.txt,
+val_1.txt, and test_1.txt).
+
+In each txt file, we provide scores in the following way:
+  <image_name> <memorability_score>
+where <image_name> has values like 00000001.jpg and <memorability_score> is a float
+value ranging from 0 to 1.
+
+Note that a particular image can have different scores in different splits because for
+each split of the data, we use a random half of the participants to find the train and 
+validation memorability scores and the other half to find the test scores i.e., both the
+images and participants for each of the splits is disjoint. This setting is the same as 
+that of prior work.
+
+Please cite the following paper if you use this dataset in your work:
+  Understanding and Predicting Image Memorability at a Large Scale
+  Aditya Khosla, Akhil S. Raju, Antonio Torralba and Aude Oliva
+  International Conference on Computer Vision (ICCV), 2015
+
+The bibtex file is available via the project website: http://memorability.csail.mit.edu
+
+For any questions or comments, please contact Aditya Khosla (khosla@csail.mit.edu).
+
+Please read the provided LICENSE file for the terms of use of this data.
+
+Copyright (c) 2015 Aditya Khosla
+
+