{"url":"/dataset/redweb-s","name":"ReDWeb-S","full_name":null,"description_markdown":"**ReDWeb-S** is a large-scale challenging dataset for Salient Object Detection. It has totally 3179 images with various real-world scenes and high-quality depth maps. The dataset is split into a training set with 2179 RGB-D image pairs and a testing set with the remaining 1000 image pairs.\n\nSource: [https://github.com/nnizhang/SMAC](https://github.com/nnizhang/SMAC)\nImage Source: [https://github.com/nnizhang/SMAC](https://github.com/nnizhang/SMAC)","description_withheld":null,"homepage":"https://github.com/nnizhang/SMAC","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-selective-mutual-attention-and","title":"Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection","first_author":"Nian Liu","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Saliency Detection","url":"/task/saliency-detection","datasets_with_task":"/datasets/task/saliency-detection"},{"name":"RGB-D Salient Object Detection","url":"/task/rgb-d-salient-object-detection","datasets_with_task":"/datasets/task/rgb-d-salient-object-detection"}],"languages":[],"variants":["ReDWeb-S"],"data_loaders":[{"repo":"https://github.com/nnizhang/SMAC","url":"https://github.com/nnizhang/SMAC","frameworks":[]}],"num_papers_in_archive":9,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"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."}