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Research questionHow can we obtain affordable, physically realistic training data for segmenting thin, self-occluding wires?Thin wires deform, overlap, and become self-occluded, making reliable instance masks difficult to collect at scale. Visually plausible synthetic images may not capture the physical wire configurations needed for models to generalize to real scenes.
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Computer Vision
Image & Video Processing
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Latest papersRecent research connected to this question, newest first.WireSeg-32K: A Physics-Grounded Synthetic Dataset for Wire Instance SegmentationThe source presents WireSeg-32K, containing 32,000 synthetic RGB images with instance masks and depth maps, generated through Cosserat-rod dynamics coupled with Isaac Sim rendering. It also includes an annotated real-world test set and reports a LoRA-fine-tuned SAM3 baseline, but the evidence is limited to the reported transfer result.research paper · Sep 2, 2026
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