{"url":"/dataset/lindenthal-camera-traps","name":"Lindenthal Camera Traps","full_name":null,"description_markdown":"This data set contains 775 video sequences, captured in the wildlife park Lindenthal (Cologne, Germany) as part of the AMMOD project, using an Intel RealSense D435 stereo camera. In addition to color and infrared images, the D435 is able to infer the distance (or “depth”) to objects in the scene using stereo vision. Observed animals include various birds (at daytime) and mammals such as deer, goats, sheep, donkeys, and foxes (primarily at nighttime). A subset of 412 images is annotated with a total of 1038 individual animal annotations, including instance masks, bounding boxes, class labels, and corresponding track IDs to identify the same individual over the entire video.\r\n\r\nSource: [Lindenthal Camera Traps on lila.science](https://lila.science/datasets/lindenthal-camera-traps/)\r\nImage Source: [Lindenthal Camera Traps on lila.science](https://lila.science/datasets/lindenthal-camera-traps/)","description_withheld":null,"homepage":"https://lila.science/datasets/lindenthal-camera-traps/","introduced_date":"2021-02-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/exploiting-depth-information-for-wildlife","title":"Exploiting Depth Information for Wildlife Monitoring","first_author":"Timm Haucke","url":null},"license":{"name":"Community Data License Agreement (permissive variant)","url":"https://cdla.dev/permissive-1-0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"},{"name":"Stereo","url":"/datasets/modality/stereo"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"Object Tracking","url":"/task/object-tracking","datasets_with_task":"/datasets/task/object-tracking"}],"languages":[],"variants":["Lindenthal Camera Traps"],"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."}