{"url":"/dataset/adobeindoornav","name":"AdobeIndoorNav","full_name":null,"description_markdown":"**AdobeIndoorNav** is a dataset collected in real-world to facilitate the research in DRL based visual navigation. The dataset includes 3D reconstruction for real-world scenes as well as densely captured real 2D images from the scenes. It provides high-quality visual inputs with real-world scene complexity to the robot at dense grid locations.","description_withheld":null,"homepage":"https://github.com/daerduoCarey/AdobeIndoorNav","introduced_date":"2018-02-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-adobeindoornav-dataset-towards-deep","title":"The AdobeIndoorNav Dataset: Towards Deep Reinforcement Learning based Real-world Indoor Robot Visual Navigation","first_author":null,"url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["AdobeIndoorNav"],"data_loaders":[{"repo":"https://github.com/daerduoCarey/AdobeIndoorNav","url":"https://github.com/daerduoCarey/AdobeIndoorNav","frameworks":[]}],"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."}