Detection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data
@article{Ron2020DetectionAS, title={Detection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data}, author={Roey Ron and Gil Elbaz}, journal={arXiv: Computer Vision and Pattern Recognition}, year={2020} }
We show a straightforward and useful methodology for performing instance segmentation using synthetic data. We apply this methodology on a basic case and derived insights through quantitative analysis. We created a new public dataset: The Expo Markers Dataset intended for detection and segmentation tasks. This dataset contains 5,000 synthetic photorealistic images with their corresponding pixel-perfect segmentation ground truth. The goal is to achieve high performance on manually-gathered and…
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