{"url":"/dataset/robobev","name":"RoboBEV","full_name":null,"description_markdown":"RoboBEV is a robustness evaluation benchmark tailored for camera-based bird's eye view (BEV) perception under natural data corruptions and domain shift. It includes eight distinct corruptions, including Bright, Dark, Fog, Snow, Motion Blur, Color Quant, Camera Crash, and Frame Lost.\r\n\r\nSource: [RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions](https://paperswithcode.com/paper/robobev-towards-robust-bird-s-eye-view)\r\n\r\nImage Source: [RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions](https://paperswithcode.com/paper/robobev-towards-robust-bird-s-eye-view)","description_withheld":null,"homepage":"https://github.com/Daniel-xsy/RoboBEV","introduced_date":"2023-04-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/robobev-towards-robust-bird-s-eye-view","title":"RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions","first_author":"Shaoyuan Xie","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Robust BEV Detection","url":"/task/robust-bev-detection","datasets_with_task":"/datasets/task/robust-bev-detection"},{"name":"Robust BEV Map Segmentation","url":"/task/robust-bev-map-segmentation","datasets_with_task":"/datasets/task/robust-bev-map-segmentation"}],"languages":[],"variants":["RoboBEV"],"data_loaders":[],"num_papers_in_archive":3,"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."}