{"url":"/dataset/hammer","name":"HAMMER","full_name":null,"description_markdown":"**HAMMER** dataset contains 13 Scenes. Each scene has two setups, with/without objects (with : scene includes several objects with various surface material, without : scene with only backgrounds - naked) and each scene has two camera trajectories. Each trajectories composed with roughly 300 frames, which adds up to 16k frames in total (13 x 2 x 2 x 300). Each trajectory contains corresponding images from each cameras : d435 – stereo, l515 – Lidar (D-ToF), polarization – RGBP (RGB with polarization), tof – (I-ToF). Each camera folder contains its intrinsic file and its own recorded images together with rendered depth GT / instance GT and camera pose. All the cameras are fully synchronized via robotic arm’s data acquisition setup.\r\n\r\nSource: [On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks](https://arxiv.org/pdf/2303.14840v1.pdf)\r\n\r\nImage Source: [On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks](https://arxiv.org/pdf/2303.14840v1.pdf)","description_withheld":null,"homepage":"https://www.campar.in.tum.de/public_datasets/2022_arxiv_jung/","introduced_date":"2023-03-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/on-the-importance-of-accurate-geometry-data","title":"On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks","first_author":"HyunJun Jung","url":null},"license":{"name":"MIT License","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Reinforcement Learning","url":"/task/reinforcement-learning","datasets_with_task":"/datasets/task/reinforcement-learning"}],"languages":[],"variants":["HAMMER"],"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":"2026-09-25T09:33:49+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."}