Datasets › TUD-L

TUD-L

Introduced by Tomas Hodan et al. in BOP: Benchmark for 6D Object Pose Estimation24 Aug 2018 archive 2025-07-28

The TUD-L (TUD Light) dataset is part of the Benchmark for 6D Object Pose Estimation (BOP). Let me provide you with some details about this dataset:

  1. Description:
  2. The TUD-L dataset focuses on lighting conditions and includes three moving objects observed under eight different illumination scenarios.
  3. It was specifically created as part of the BOP benchmark to evaluate 6D object pose estimation methods.

  4. Object Instances:

  5. The dataset contains three objects:

    • Dragon
    • Frog
    • Watering pot
  6. Challenges:

  7. TUD-L introduces challenging illumination variations to test the robustness of pose estimation algorithms.
  8. Unlike other datasets, TUD-L has limited clutter and occlusion, making it suitable for evaluating lighting-specific performance.

  9. Ground-Truth Annotations:

  10. The dataset provides ground-truth 6D object poses, 2D bounding boxes, and 2D binary masks for the training and test RGB-D images.
  11. These annotations enable researchers to evaluate their algorithms accurately.

  12. Usage:

  13. Researchers can use the TUD-L dataset to develop and evaluate 6D object pose estimation methods under varying lighting conditions.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 34 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • TUD-L

1 variant name, as the archive lists them.

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