We present below a sample dataset collected using our framework for synthetic data collection that is efficient in terms of time taken to collect and annotate data, and which makes use of free and open source software tools and 3D assets. Our approach provides a large number of systematic variations in synthetic image generation parameters. The approach is highly effective, resulting in a deep learning model with a top-1 accuracy of 72% on the ObjectNet data, which is a new state-of-the-art result.

Dataset Files

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[1] Sai Abinesh Natarajan, Michael Madden, "Hybrid Synthetic Data that Outperforms Real Data in ObjectNet ", IEEE Dataport, 2021. [Online]. Available: http://dx.doi.org/10.21227/x84r-vh21. Accessed: May. 17, 2022.
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doi = {10.21227/x84r-vh21},
url = {http://dx.doi.org/10.21227/x84r-vh21},
author = {Sai Abinesh Natarajan; Michael Madden },
publisher = {IEEE Dataport},
title = {Hybrid Synthetic Data that Outperforms Real Data in ObjectNet },
year = {2021} }
TY - DATA
T1 - Hybrid Synthetic Data that Outperforms Real Data in ObjectNet
AU - Sai Abinesh Natarajan; Michael Madden
PY - 2021
PB - IEEE Dataport
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Sai Abinesh Natarajan, Michael Madden. (2021). Hybrid Synthetic Data that Outperforms Real Data in ObjectNet . IEEE Dataport. http://dx.doi.org/10.21227/x84r-vh21
Sai Abinesh Natarajan, Michael Madden, 2021. Hybrid Synthetic Data that Outperforms Real Data in ObjectNet . Available at: http://dx.doi.org/10.21227/x84r-vh21.
Sai Abinesh Natarajan, Michael Madden. (2021). "Hybrid Synthetic Data that Outperforms Real Data in ObjectNet ." Web.
1. Sai Abinesh Natarajan, Michael Madden. Hybrid Synthetic Data that Outperforms Real Data in ObjectNet [Internet]. IEEE Dataport; 2021. Available from : http://dx.doi.org/10.21227/x84r-vh21
Sai Abinesh Natarajan, Michael Madden. "Hybrid Synthetic Data that Outperforms Real Data in ObjectNet ." doi: 10.21227/x84r-vh21