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SIDOD: A synthetic image dataset for 3D object pose recognition with distractors

Publication ,  Conference
Jalal, M; Spjut, J; Boudaoud, B; Betke, M
Published in: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
June 1, 2019

We present a new, publicly-available image dataset generated by the NVIDIA Deep Learning Data Synthesizer intended for use in object detection, pose estimation, and tracking applications. This dataset contains 144k stereo image pairs that synthetically combine 18 camera viewpoints of three photorealistic virtual environments with up to 10 objects (chosen randomly from the 21 object models of the YCB dataset ) and flying distractors. Object and camera pose, scene lighting, and quantity of objects and distractors were randomized. Each provided view includes RGB, depth, segmentation, and surface normal images, all pixel level. We describe our approach for domain randomization and provide insight into the decisions that produced the dataset.

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Published In

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

DOI

EISSN

2160-7516

ISSN

2160-7508

Publication Date

June 1, 2019

Volume

2019-June

Start / End Page

475 / 477
 

Citation

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Jalal, M., Spjut, J., Boudaoud, B., & Betke, M. (2019). SIDOD: A synthetic image dataset for 3D object pose recognition with distractors. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (Vol. 2019-June, pp. 475–477). https://doi.org/10.1109/CVPRW.2019.00063
Jalal, M., J. Spjut, B. Boudaoud, and M. Betke. “SIDOD: A synthetic image dataset for 3D object pose recognition with distractors.” In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2019-June:475–77, 2019. https://doi.org/10.1109/CVPRW.2019.00063.
Jalal M, Spjut J, Boudaoud B, Betke M. SIDOD: A synthetic image dataset for 3D object pose recognition with distractors. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2019. p. 475–7.
Jalal, M., et al. “SIDOD: A synthetic image dataset for 3D object pose recognition with distractors.” IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2019-June, 2019, pp. 475–77. Scopus, doi:10.1109/CVPRW.2019.00063.
Jalal M, Spjut J, Boudaoud B, Betke M. SIDOD: A synthetic image dataset for 3D object pose recognition with distractors. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2019. p. 475–477.

Published In

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

DOI

EISSN

2160-7516

ISSN

2160-7508

Publication Date

June 1, 2019

Volume

2019-June

Start / End Page

475 / 477