{"url":"/dataset/void","name":"VOID","full_name":"Visual Odometry with Inertial and Depth","description_markdown":"The dataset was collected using the Intel RealSense D435i camera, which was configured to produce synchronized accelerometer and gyroscope measurements at 400 Hz, along with synchronized VGA-size (640 x 480) RGB and depth streams at 30 Hz. The depth frames are acquired using active stereo and is aligned to the RGB frame using the sensor factory calibration. All the measurements are timestamped.\r\n\r\nThe dataset contains 56 sequences in total, both indoor and outdoor with challenging motion. Typical scenes include classrooms, offices, stairwells, laboratories, and gardens. Of the 56 sequences, 48 sequences (approximately 47K frames) are designated for training and 8 sequences for testing, from which we sampled 800 frames to construct the testing set. Each sequence constains sparse depth maps at three density levels, 1500, 500 and 150 points, corresponding to 0.5%, 0.15% and 0.05% of VGA size.","description_withheld":null,"homepage":"https://github.com/alexklwong/void-dataset","introduced_date":"2019-05-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/190508616","title":"Unsupervised Depth Completion from Visual Inertial Odometry","first_author":"Alex Wong","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Depth Completion","url":"/task/depth-completion","datasets_with_task":"/datasets/task/depth-completion"}],"languages":[],"variants":["VOID"],"data_loaders":[],"num_papers_in_archive":26,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/depth-completion-on-void","task":"Depth Completion","dataset_variant":"VOID","rows":6,"metrics":["MAE","RMSE","iMAE","iRMSE"],"first_row_in_archive_order":{"model":"NLSPN","paper":"/paper/non-local-spatial-propagation-network-for","metrics":{"MAE":"26.736","RMSE":"79.121","iMAE":"12.703","iRMSE":"33.876"},"code_links":[{"title":"zzangjinsun/NLSPN_ECCV20","url":"https://github.com/zzangjinsun/NLSPN_ECCV20"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/unsupervised-depth-completion-with-calibrated","title":"Unsupervised Depth Completion with Calibrated Backprojection Layers","date":"2021-08-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-topology-from-synthetic-data-for","title":"Learning Topology from Synthetic Data for Unsupervised Depth Completion","date":"2021-06-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/non-local-spatial-propagation-network-for","title":"Non-Local Spatial Propagation Network for Depth Completion","date":"2020-07-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/190508616","title":"Unsupervised Depth Completion from Visual Inertial Odometry","date":"2019-05-15","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/dense-depth-posterior-ddp-from-single-image","title":"Dense Depth Posterior (DDP) from Single Image and Sparse Range","date":"2019-01-28","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/self-supervised-sparse-to-dense-self","title":"Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera","date":"2018-07-01","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":7,"samples_ran":3,"samples_unverified":4,"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."}