{"url":"/dataset/spectrovision","name":"SpectroVision","full_name":null,"description_markdown":"**SpectroVision** is a dataset of 14,400 high resolution texture images and spectral measurements collected from a PR2 mobile manipulator that interacted with 144 household objects from eight material categories.\n\nSource: [https://github.com/Healthcare-Robotics/spectrovision](https://github.com/Healthcare-Robotics/spectrovision)\nImage Source: [https://github.com/Healthcare-Robotics/spectrovision](https://github.com/Healthcare-Robotics/spectrovision)","description_withheld":null,"homepage":"https://github.com/Healthcare-Robotics/spectrovision","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/multimodal-material-classification-for-robots","title":"Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging","first_author":"Zackory Erickson","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Material Classification","url":"/task/material-classification","datasets_with_task":"/datasets/task/material-classification"},{"name":"Material Recognition","url":"/task/material-recognition","datasets_with_task":"/datasets/task/material-recognition"}],"languages":[],"variants":["SpectroVision"],"data_loaders":[{"repo":"https://github.com/Healthcare-Robotics/spectrovision","url":"https://github.com/Healthcare-Robotics/spectrovision","frameworks":["pytorch"]}],"num_papers_in_archive":1,"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."}