Photorealistic Image Synthesis for Object Instance Detection

9 Feb 2019Tomas HodanVibhav VineetRan GalEmanuel ShalevJon HanzelkaTreb ConnellPedro UrbinaSudipta N. SinhaBrian Guenter

We present an approach to synthesize highly photorealistic images of 3D object models, which we use to train a convolutional neural network for detecting the objects in real images. The proposed approach has three key ingredients: (1) 3D object models are rendered in 3D models of complete scenes with realistic materials and lighting, (2) plausible geometric configuration of objects and cameras in a scene is generated using physics simulations, and (3) high photorealism of the synthesized images achieved by physically based rendering... (read more)

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