{"url":"/dataset/motfront","name":"MOTFront","full_name":null,"description_markdown":"MOTFront provides photo-realistic RGB-D images with their corresponding instance segmentation masks, class labels, 2D & 3D bounding boxes, 3D geometry, 3D poses and camera parameters. The MOTFront dataset comprises 2,381 unique indoor sequences with a total of 60,000 images and is based on the 3D-FRONT dataset.","description_withheld":null,"homepage":"https://domischmauser.github.io/3D_MOT/","introduced_date":"2022-06-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/3d-multi-object-tracking-with-differentiable","title":"3D Multi-Object Tracking with Differentiable Pose Estimation","first_author":"Dominik Schmauser","url":null},"license":null,"modalities":[],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"3D Multi-Object Tracking","url":"/task/3d-multi-object-tracking","datasets_with_task":"/datasets/task/3d-multi-object-tracking"},{"name":"3D Object Tracking","url":"/task/3d-object-tracking","datasets_with_task":"/datasets/task/3d-object-tracking"}],"languages":[],"variants":["MOTFront"],"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."}