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We present a system for training deep neural networks for object detection using synthetic images.
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X. Peng, B. Sun, K. Ali, and K. Saenko · 2015
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The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes
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Cut, paste and learn: Surprisingly easy synthesis for instance detection
D. Dwibedi, I. Misra, and M. Hebert · 2017
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On pre-trained image features and synthetic images for deep learning
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Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task
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Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
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Scenenet RGB-D: Can 5M synthetic images beat generic ImageNet pre-training on indoor segmentation?
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Sim4CV: A photo-realistic simulator for computer vision applications
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Domain randomization for transferring deep neural networks from simulation to the real world
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