{"url":"/dataset/drunkard-s-dataset","name":"Drunkard's Dataset","full_name":null,"description_markdown":"Estimating camera motion in deformable scenes poses a complex and open research challenge. Most existing non-rigid structure from motion techniques assume to observe also static scene parts besides deforming scene parts in order to establish an anchoring reference. However, this assumption does not hold true in certain relevant application cases such as endoscopies. To tackle this issue with a common benchmark, we introduce the Drunkard’s Dataset, a challenging collection of synthetic data targeting visual navigation and reconstruction in deformable environments. This dataset is the first large set of exploratory camera trajectories with ground truth inside 3D scenes where every surface exhibits non-rigid deformations over time. Simulations in realistic 3D buildings lets us obtain a vast amount of data and ground truth labels, including camera poses, RGB images and depth, optical flow and normal maps at high resolution and quality.","description_withheld":null,"homepage":"https://davidrecasens.github.io/TheDrunkard'sOdometry/","introduced_date":"2023-06-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-drunkard-s-odometry-estimating-camera","title":"The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes","first_author":"David Recasens","url":null},"license":{"name":"MIT License","url":"https://github.com/UZ-SLAMLab/DrunkardsOdometry/blob/12a330d8af614f15245a7c7cc2afc0d13d6d0d35/LICENSE"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Medical","url":"/datasets/modality/medical"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"3D Reconstruction","url":"/task/3d-reconstruction","datasets_with_task":"/datasets/task/3d-reconstruction"},{"name":"Visual Tracking","url":"/task/visual-tracking","datasets_with_task":"/datasets/task/visual-tracking"},{"name":"Pose Tracking","url":"/task/pose-tracking","datasets_with_task":"/datasets/task/pose-tracking"},{"name":"Single-View 3D Reconstruction","url":"/task/single-view-3d-reconstruction","datasets_with_task":"/datasets/task/single-view-3d-reconstruction"},{"name":"Visual Odometry","url":"/task/visual-odometry","datasets_with_task":"/datasets/task/visual-odometry"},{"name":"6D Pose Estimation","url":"/task/6d-pose-estimation-1","datasets_with_task":"/datasets/task/6d-pose-estimation-1"},{"name":"6D Pose Estimation using RGBD","url":"/task/6d-pose-estimation-using-rgbd","datasets_with_task":"/datasets/task/6d-pose-estimation-using-rgbd"},{"name":"3D Pose Estimation","url":"/task/3d-pose-estimation","datasets_with_task":"/datasets/task/3d-pose-estimation"},{"name":"6D Pose Estimation using RGB","url":"/task/6d-pose-estimation","datasets_with_task":"/datasets/task/6d-pose-estimation"},{"name":"Pose Prediction","url":"/task/pose-prediction","datasets_with_task":"/datasets/task/pose-prediction"},{"name":"Simultaneous Localization and Mapping","url":"/task/simultaneous-localization-and-mapping","datasets_with_task":"/datasets/task/simultaneous-localization-and-mapping"},{"name":"Drone Pose Estimation","url":"/task/drone-pose-estimation","datasets_with_task":"/datasets/task/drone-pose-estimation"},{"name":"Real-Time Visual Tracking","url":"/task/real-time-visual-tracking","datasets_with_task":"/datasets/task/real-time-visual-tracking"},{"name":"Monocular Visual Odometry","url":"/task/monocular-visual-odometry","datasets_with_task":"/datasets/task/monocular-visual-odometry"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Drunkard's Dataset","Drunkard's Dataset Level3 Scene0"],"data_loaders":[{"repo":"https://github.com/UZ-SLAMLab/DrunkardsOdometry","url":"https://github.com/UZ-SLAMLab/DrunkardsOdometry","frameworks":["pytorch"]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/6d-pose-estimation-using-rgbd-on-drunkard-s","task":"6D Pose Estimation using RGBD","dataset_variant":"Drunkard's Dataset Level3 Scene0","rows":1,"metrics":["Absolute Trajectory Error [m]","Relative Position Error Rotation [º]","Relative Position Error Translation [cm]"],"first_row_in_archive_order":{"model":"Drunkard's Odometry","paper":"/paper/the-drunkard-s-odometry-estimating-camera","metrics":{"Absolute Trajectory Error [m]":"1.74","Relative Position Error Rotation [º]":"0.48","Relative Position Error Translation [cm]":"1.82"},"code_links":[{"title":"UZ-SLAMLab/DrunkardsOdometry","url":"https://github.com/UZ-SLAMLab/DrunkardsOdometry"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/the-drunkard-s-odometry-estimating-camera","title":"The Drunkard's Odometry: Estimating Camera Motion in Deforming Scenes","date":"2023-06-29","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"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."}