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11 results for “6D pose estimation”

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zenodo40/100

DoPose: dataset for object segmentation and 6D pose estimation

<p>DoPose (Dortmund Pose)is a dataset of highly cluttered and closely stacked objects. The dataset is saved in the <a href="https://github.com/thodan/bop_toolkit/blob/master/docs/bop_datasets_format.md">BOP format</a>. The dataset includes RGB images, Depth images, 6D Pose of objects, segmentation mask (all and visible), COCO Json annotation, camera transformations, and 3D model of all objects. The dataset contains 2 different types of scenes (table and bin). Each scene contains different view angles. For the bin scenes, the data contains 183 scenes with 2150 image views. In those 183 scenes 35 scenes contain 2 views, 20 contains 3 views and 128 contains 16 views. And for table scenes, the data contains 118 scenes with 1175 image views. in Those 118 scenes, 20 scenes contain 3 views, 50 scenes with 6 images, and 48 scenes with 17 images. So in total, our data contains 301 scenes and 3325 view images. Most of the scenes contain mixed objects. The dataset contains 19 objects in total.</p> <p>For more info about the dataset content and collection process&nbsp;please refer to our <a href="https://arxiv.org/abs/2204.13613">Arxiv preprint</a></p> <p>If you have any questions about the dataset, please contact <strong>anas.gouda@tu-dortmund.de</strong></p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

INTELLIMAN_WP2_Application Requirements and Integration_T2.4_Fresh food handling use case analysis, integration and validation_Apple 6D pose estimation dataset_v0

<p>The dataset contains the data generated for the training of the 6D pose estimation neural network<br>DOPE related to the publication:<br>M. Costanzo, M. De Simone, S. Federico, C. Natale and S. Pirozzi, "Enhanced 6D Pose Estimation for<br>Robotic Fruit Picking," 2023 9th International Conference on Control, Decision and Information<br>Technologies (CoDIT), Rome, Italy, 2023, pp. 901-906, doi: 10.1109/CoDIT58514.2023.10284072.</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - Corner Clamp Part 1

<p>@article{schieber2024asdf,<br>&nbsp; title={ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation},<br>&nbsp; author={Schieber, Hannah and Li, Shiyu and Corell, Niklas and Beckerle, Philipp and Kreimeier, Julian and Roth, Daniel},<br>&nbsp; journal={arXiv preprint arXiv:2403.16400},<br>&nbsp; year={2024}<br>}</p>

opencc-by-4.0May 2024View details →
zenodo32/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - Corner Clamp Part 2 - Geared Caliper Base

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opencc-by-4.0May 2024View details →
zenodo32/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - NanoVise part 1

<p>@article{schieber2024asdf,<br>&nbsp; title={ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation},<br>&nbsp; author={Schieber, Hannah and Li, Shiyu and Corell, Niklas and Beckerle, Philipp and Kreimeier, Julian and Roth, Daniel},<br>&nbsp; journal={arXiv preprint arXiv:2403.16400},<br>&nbsp; year={2024}<br>}</p>

opencc-by-4.0May 2024View details →
zenodo32/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - NanoVise part 2

<p>@article{schieber2024asdf,<br>&nbsp; title={ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation},<br>&nbsp; author={Schieber, Hannah and Li, Shiyu and Corell, Niklas and Beckerle, Philipp and Kreimeier, Julian and Roth, Daniel},<br>&nbsp; journal={arXiv preprint arXiv:2403.16400},<br>&nbsp; year={2024}<br>}</p>

opencc-by-4.0May 2024View details →
zenodo32/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - Hand Screw Clamp

<p>@article{schieber2024asdf,<br>&nbsp; title={ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation},<br>&nbsp; author={Schieber, Hannah and Li, Shiyu and Corell, Niklas and Beckerle, Philipp and Kreimeier, Julian and Roth, Daniel},<br>&nbsp; journal={arXiv preprint arXiv:2403.16400},<br>&nbsp; year={2024}<br>}</p>

opencc-by-4.0May 2024View details →
zenodo28/100

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans - Dataset Other

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opencc-by-4.0Dec 2021View details →
zenodo28/100

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans - Dataset Synth

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opencc-by-4.0Jul 2024View details →
zenodo28/100

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans - Dataset Greybox

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opencc-by-4.0Jul 2024View details →
zenodo28/100

ASDF: Assembly State Detection Utilizing Late Fusion by Integrating 6D Pose Estimation - Training Set - Hand Screw Clamp Part 2

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opencc-by-4.0Sep 2024View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record