{"url":"/dataset/timbervision-dataset","name":"TimberVision","full_name":"TimberVision","description_markdown":"The TimberVision dataset consists of more than 2k annotated RGB images and contains a total of 51k trunk components including cut and lateral surfaces, thereby surpassing any existing dataset in this domain in terms of both quantity and detail by a large margin. The dataset can be used to  train oriented object detection and instance segmentation and evaluate the influence of multiple scene parameters on model performance. Additionally, a generic framework is provided to fuse the components detected by the models for both tasks into unified trunk representations. Furthermore, geometric properties are derived automatically and multi-object tracking is applied to further enhance robustness.","description_withheld":null,"homepage":"https://github.com/timbervision/timbervision","introduced_date":"2025-01-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/timbervision-a-multi-task-dataset-and","title":"TimberVision: A Multi-Task Dataset and Framework for Log-Component Segmentation and Tracking in Autonomous Forestry Operations","first_author":"Daniel Steininger","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"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"},{"name":"Panoptic Segmentation","url":"/task/panoptic-segmentation","datasets_with_task":"/datasets/task/panoptic-segmentation"},{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"},{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Oriented Object Detection","url":"/task/oriented-object-detection","datasets_with_task":"/datasets/task/oriented-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["TimberVision"],"data_loaders":[{"repo":"https://github.com/timbervision/timbervision","url":"https://github.com/timbervision/timbervision","frameworks":[]}],"num_papers_in_archive":1,"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."}