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# Welcome to GenImageNet This [OSF repository](https://osf.io/8ctjy/) hosts the AI-generated images from the paper: [The power of generative marketing: Can generative AI create superhuman visual marketing content?](https://doi.org/10.1016/j.ijresmar.2024.09.002). ## Overview of the dataset The dataset includes a total of 10,320 AI-generated images: | | DALL-E 3 | Firefly 2 | Imagen 2 | Imagine | Midjourney v6 | Realistic Vision | SDXL Turbo | Total | |-------------------|-----------|-----------|----------|---------|---------------|------------------|------------|------------| | amazon | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | booking_com | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | image_ads | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | instagram | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | lions_awards | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | twitter | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | unsplash | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | yelp | 300 | 30 | 30 | 30 | 300 | 300 | 300 | 1,290 | | **Total** | **2,400** | **240** | **240** | **240** | **2,400** | **2,400** | **2,400** | **10,320** | The CSV and XLSX files **GenImageNet_imageLevel** and **GenImageNet_assignmentLevel** include the following variables per image and assignmentId, respectively: | Variable | Description | |---------------------|------------------------------------------------------------------------------| | aestheticsScore | Neural Image Assessment (NIMA) score | | assignmentId | Unique ID of a task completed by a specific workerId | | colorSaturation | Sum of mean and standard deviation of S values in HSV color space | | dataset | Origin of the human-made source image | | filename | Filename of the AI-generated image (see below for naming convention) | | hasFace | Binary flag to indicate if a face is displayed on the image (via MTCNN) | | hasText | Binary flag to indicate if text is displayed on the image (via tesseract) | | hasVisibleWatermark | Binary flag to indicate if a visual watermark is visible on the image | | model | AI model used for image generation | | prompt | Input prompt used to generate the image with the given AI model | | qualityScore | 7-point Likert rating for perceived quality for the given assignmentId | | realismScore | 7-point Likert rating for perceived realism for the given assignmentId | | visualComplexity | File size in kilobyte divided by the image resolution (i.e., width × height) | | workerId | Unique ID per worker/rater | ## Naming convention for filenames Filenames are coded as follows: <_model_id_>\_<_dataset_id_>\_<_image_incrementor_>.webp The assoicated keys are: | _model_id_ | model_name | |----------|------------------| | 1 | DALL-E 3 | | 2 | Midjourney v6 | | 3 | Firefly 2 | | 4 | Imagen 2 | | 5 | Imagine | | 6 | Realistic Vision | | 7 | SDXL Turbo | | _dataset_id_ | dataset_name | |------------|----------------| | a | Amazon | | b | Booking.com | | c | Image ads | | d | Instagram | | e | Lions awards | | f | Twitter | | g | Unsplash | | h | Yelp | _image_incrementor_ is a 4 digit integer value ### Examples: - _1_b_1048.webp_ is an image generated by _DALL-E 3_ based on an image from the _Booking.com_ dataset. - _6_a_0029.webp_ is an image generated by _Realistic Vision_ based on an image from the _Amazon_ dataset. # License This dataset is published under **CC BY-NC-ND 4.0** For more information see: https://creativecommons.org/licenses/by-nc-nd/4.0/ Please use the following citation when using this dataset: J. Hartmann, Y. Exner, S. Domdey, The power of generative marketing: Can generative AI create superhuman visual marketing content?, International Journal of Research in Marketing (2024), doi: https://doi.org/10.1016/j.ijresmar.2024.09.002
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