ArticleData in brief2026
Cross domain additive manufacturing video object segmentation dataset.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
This article presents labeled data collected from video footage of additive manufacturing processes. This computer vision dataset contains 90 labeled additive manufacturing video segments across four distinct additive manufacturing processes, amounting to 900 labeled, object instance video frames. The technologies covered by the dataset include laser hot-wire additive manufacturing (LHW-DED), plasma arc welding (PAW), tungsten inert gas wire arc additive manufacturing (TIG-WAAM), and polymer-based additive manufacturing (visPolymer and irPolymer). For each of the manufacturing processes, build deposition video was captured and then randomly sampled into 10 frame-long video segments. Depending on the manufacturing process, two of the following four object instance classes are labeled in each frame: Melt Pool, Feed Wire, Nozzle, and Material. Since the dataset's directory organization follows that of common video object segmentation (VOS) datasets, such as coMplex video Object SEgmentation (MOSE), MOSEv2, Densely Annotated Video Segmentation (DAVIS), and YouTube-VOS, it can be easily integrated into other VOS model training pipelines for foundation model fine-tuning, training, or inference capability testing. This dataset provides researchers access to labeled additive manufacturing object instances for VOS tasks.
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