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The advancement of computer graphics and VR provides numerous opportunity of AI researchers. In this project, we are developing realistic virtual worlds using computer graphics and generative models to develop and evaluate computer vision models. Our work includes: developing software infrastructure [1], train computer vision models using synthetic images [2], stress-test vision algorithms [3,4] and domain adaptation. This project is supported by DIVA and Visual Cortex On Silicon.

[1] Weichao Qiu, Alan Yuille, UnrealCV: Connecting Computer Vision to Unreal Engine, ECCV Workshop VARVAI 2016
[2] Siyuan Qiao, Wei Shen, Weichao Qiu, Chenxi Liu, and Alan Yuille. ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond, ICCV 2017
[3] Yi Zhang, Weichao Qiu, Qi Chen, Xiaolin Hu, and Alan Yuille. Unrealstereo: A synthetic dataset for analyzing stereo vision, arXiv preprint 2016
[4] Xiaohui Zeng, Chenxi Liu, Yu-Siang Wang, Weichao Qiu, Lingxi Xie, Yu-Wing Tai, Chi Keung Tang, Alan Yuille. Adversarial Attacks Beyond the Image Space, arXiv preprint 2017