TransBiolab: A Real-World Multi-View Dataset of Cluttered Transparent Biomedical Objects
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TL;DR - TransBiolab is a large real-world RGB-D dataset for perceiving cluttered, transparent biomedical labware from calibrated multi-view sequences. It targets segmentation, depth, pose estimation, and robotic manipulation under realistic occlusion and viewpoint changes.
- Contains 161,315 frames from 98 scenes and 1.03 million instance annotations across 15 object types.
- Provides 6D poses, full and visible masks, depth data, and per-frame camera calibration.
- Organizes difficulty by object category, object count, and camera viewpoint.
- Defines benchmarks for segmentation, depth estimation and completion, 6D pose estimation, and system-level robot manipulation.
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TransBiolab: A Real-World Multi-View Dataset of Cluttered Transparent Biomedical Objects
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Semantic Scholar citations 1 · Semantic Scholar influential citations 0
TL;DR - TransBiolab is a large real-world RGB-D dataset for perceiving cluttered, transparent biomedical labware from calibrated multi-view sequences. It targets segmentation, depth, pose estimation, and robotic manipulation under realistic occlusion and viewpoint changes.
- Contains 161,315 frames from 98 scenes and 1.03 million instance annotations across 15 object types.
- Provides 6D poses, full and visible masks, depth data, and per-frame camera calibration.
- Organizes difficulty by object category, object count, and camera viewpoint.
- Defines benchmarks for segmentation, depth estimation and completion, 6D pose estimation, and system-level robot manipulation.