{"url":"/dataset/salicon","name":"SALICON","full_name":"Salicency in Context","description_markdown":"The SALIency in CONtext (**SALICON**) dataset contains 10,000 training images, 5,000 validation images and 5,000 test images for saliency prediction. This dataset has been created by annotating saliency in images from MS COCO.\r\nThe ground-truth saliency annotations include fixations generated from mouse trajectories. To improve the data quality, isolated fixations with low local density have been excluded.\r\nThe training and validation sets, provided with ground truth, contain the following data fields: image, resolution and gaze.\r\nThe testing data contains only the image and resolution fields.\r\n\r\nSource: [DeepFix: A Fully Convolutional Neural Network for predicting Human Eye Fixations](https://arxiv.org/abs/1510.02927)\r\nImage Source: [http://salicon.net/explore/](http://salicon.net/explore/)","description_withheld":null,"homepage":"http://salicon.net/","introduced_date":"2015-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/salicon-saliency-in-context","title":"SALICON: Saliency in Context","first_author":"Ming Jiang","url":null},"license":{"name":"Creative Commons Attribution 4.0 License","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Saliency Prediction","url":"/task/saliency-prediction","datasets_with_task":"/datasets/task/saliency-prediction"},{"name":"Few-Shot Transfer Learning for Saliency Prediction","url":"/task/saliency-prediction-1","datasets_with_task":"/datasets/task/saliency-prediction-1"}],"languages":[],"variants":["SALICON->WebpageSaliency - 1-shot","SALICON->WebpageSaliency - 5-shot ","SALICON->WebpageSaliency - 10-shot ","SALICON->WebpageSaliency - EUB","SALICON"],"data_loaders":[],"num_papers_in_archive":161,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/saliency-prediction-on-salicon","task":"Saliency Prediction","dataset_variant":"SALICON","rows":5,"metrics":["AUC","CC","KLD","NSS","SIM","sAUC","IG"],"first_row_in_archive_order":{"model":"SUM","paper":"/paper/sum-saliency-unification-through-mamba-for","metrics":{"AUC":"0.876","CC":"0.909","KLD":"0.192","NSS":"1.981","SIM":"0.804"},"code_links":[{"title":"Arhosseini77/SUM","url":"https://github.com/Arhosseini77/SUM"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-transfer-learning-on-salicon","task":"Few-Shot Transfer Learning for Saliency Prediction","dataset_variant":"SALICON->WebpageSaliency - 1-shot","rows":2,"metrics":["NSS","AUC","CC"],"first_row_in_archive_order":{"model":"DINet+FT|Ref","paper":"/paper/n-reference-transfer-learning-for-saliency","metrics":{"AUC":"0.8051","CC":"0.6121","NSS":"1.5077"},"code_links":[{"title":"luoyan407/n-reference","url":"https://github.com/luoyan407/n-reference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-transfer-learning-on-salicon-1","task":"Few-Shot Transfer Learning for Saliency Prediction","dataset_variant":"SALICON->WebpageSaliency - 5-shot","rows":1,"metrics":["NSS","AUC","CC"],"first_row_in_archive_order":{"model":"DINet+FT|Ref","paper":"/paper/n-reference-transfer-learning-for-saliency","metrics":{"AUC":"0.8200","CC":"0.6468","NSS":"1.6085"},"code_links":[{"title":"luoyan407/n-reference","url":"https://github.com/luoyan407/n-reference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-transfer-learning-on-salicon-2","task":"Few-Shot Transfer Learning for Saliency Prediction","dataset_variant":"SALICON->WebpageSaliency - 10-shot","rows":1,"metrics":["NSS","AUC","CC"],"first_row_in_archive_order":{"model":"DINet+FT|Ref","paper":"/paper/n-reference-transfer-learning-for-saliency","metrics":{"AUC":"0.8276","CC":"0.6605","NSS":"1.6439"},"code_links":[{"title":"luoyan407/n-reference","url":"https://github.com/luoyan407/n-reference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-transfer-learning-on-salicon-3","task":"Few-Shot Transfer Learning for Saliency Prediction","dataset_variant":"SALICON->WebpageSaliency - EUB","rows":1,"metrics":["NSS","AUC","CC"],"first_row_in_archive_order":{"model":"DINet+FT|Ref","paper":"/paper/n-reference-transfer-learning-for-saliency","metrics":{"AUC":"0.8494","CC":"0.7442","NSS":"1.8831"},"code_links":[{"title":"luoyan407/n-reference","url":"https://github.com/luoyan407/n-reference"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/salnas-efficient-saliency-prediction-neural","title":"SalNAS: Efficient Saliency-prediction Neural Architecture Search with self-knowledge distillation","date":"2024-07-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sum-saliency-unification-through-mamba-for","title":"SUM: Saliency Unification through Mamba for Visual Attention Modeling","date":"2024-06-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":14,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mds-vitnet-improving-saliency-prediction-for","title":"MDS-ViTNet: Improving saliency prediction for Eye-Tracking with Vision Transformer","date":"2024-05-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/tempsal-uncovering-temporal-information-for-1","title":"TempSAL - Uncovering Temporal Information for Deep Saliency Prediction","date":"2023-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/transalnet-visual-saliency-prediction-using","title":"TranSalNet: Towards perceptually relevant visual saliency prediction","date":"2021-10-07","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":6,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/n-reference-transfer-learning-for-saliency","title":"$n$-Reference Transfer Learning for Saliency Prediction","date":"2020-07-09","rows_on_this_dataset":5,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":25,"samples_ran":20,"samples_unverified":5,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}