{"url":"/dataset/dispscenes","name":"DispScenes","full_name":null,"description_markdown":"The **DispScenes** dataset was created to address the specific problem of disparate image matching. The image pairs in all the datasets exhibit high levels of variation in illumination and viewpoint and also contain instances of occlusion. The DispScenes dataset provides manual ground truth keypoint correspondences for all images.\n\nSource: [Matching Disparate Image Pairs Using Shape-Aware ConvNets](https://arxiv.org/abs/1811.09889)","description_withheld":null,"homepage":null,"introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-spectral-correspondence-for-matching","title":"Deep Spectral Correspondence for Matching Disparate Image Pairs","first_author":"Arun CS Kumar","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Graph Matching","url":"/task/graph-matching","datasets_with_task":"/datasets/task/graph-matching"},{"name":"Matching Disparate Images","url":"/task/matching-disparate-images","datasets_with_task":"/datasets/task/matching-disparate-images"}],"languages":[],"variants":["DispScenes"],"data_loaders":[],"num_papers_in_archive":2,"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."}