behavior-in-the-wild
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README.md
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num_examples: 219
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download_size: 2551503
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dataset_size: 6102866
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configs:
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- config_name: default
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data_files:
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path: data/train-*
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- split: test
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path: data/test-*
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---
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## Dataset Description
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- **Website:** https://behavior-in-the-wild.github.io/memorability.html
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- **Paper:** https://arxiv.org/
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### Dataset Summary
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LAMDBA is a long term ad memorability dataset, featuring data from 1749 participants and 2205 ads across 276 brands.
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- `youtube_id`: youtube id for the video
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- `ad_details`: scene by scene features for each video
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num_bytes: 612243.5428309665
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num_examples: 219
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download_size: 2551503
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dataset_size: 6102866
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configs:
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- config_name: default
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data_files:
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path: data/train-*
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- split: test
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path: data/test-*
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license: mit
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pretty_name: Long Term Memorability of Advertisements (LAMBDA)
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---
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## Dataset Description
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- **Website:** https://behavior-in-the-wild.github.io/memorability.html
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- **Paper:** https://arxiv.org/abs/2309.00378
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### Dataset Summary
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LAMDBA is a long term ad memorability dataset, featuring data from 1749 participants and 2205 ads across 276 brands.
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- `youtube_id`: youtube id for the video
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- `ad_details`: scene by scene features for each video
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## Citation
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@misc{s2024longtermadmemorabilityunderstanding,
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title={Long-Term Ad Memorability: Understanding and Generating Memorable Ads},
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author={Harini S I au2 and Somesh Singh and Yaman K Singla and Aanisha Bhattacharyya and Veeky Baths and Changyou Chen and Rajiv Ratn Shah and Balaji Krishnamurthy},
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year={2024},
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eprint={2309.00378},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2309.00378}}
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