{"url":"/dataset/kitti-motion","name":"KITTI-Motion","full_name":"KITTI-Motion","description_markdown":"The **KITTI-Motion** dataset contains pixel-wise semantic class labels and moving object annotations for 255 images taken from the KITTI Raw dataset. The images are of resolution 1280×384 pixels and contain scenes of freeways, residential areas and inner-cities. The task is not just to semantically segment objects but also to identify their motion status.\n\nSource: [http://deepmotion.cs.uni-freiburg.de/](http://deepmotion.cs.uni-freiburg.de/)\nImage Source: [http://deepmotion.cs.uni-freiburg.de/](http://deepmotion.cs.uni-freiburg.de/)","description_withheld":null,"homepage":"http://deepmotion.cs.uni-freiburg.de/","introduced_date":"2017-01-01","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["KITTI-Motion"],"data_loaders":[],"num_papers_in_archive":0,"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."}