Learning from Simulated and Unsupervised Images through Adversarial Training

Ashish Shrivastava, Tomas Pfister, Oncel Tuzel +3

With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations. However, learning from…