Shengqu Cai
蔡盛曲

I am an incoming CS PhD student at Stanford University and a research scientist intern at Adobe Research.
Previously, I was a CS master student at ETH Zürich supervised by Prof. Luc Van Gool.
In 2022, I spent a wonderful half a year visiting Stanford University at the Computational Imaging Lab led by Prof. Gordon Wetzstein, working on scene extrapolation.
Before this, I obtained my Bachelor degree in Computer Science with first honour from King's College London in United Kingdom, working on unsupervised learning.

I am interested in using artificial intelligence to solve tasks that are fundamentally ill-posed via traditional methods, slay the unslayable. I have been working primarily around neural rendering and 3D vision, including but not limited to generative models, inverse rendering, unsupervised learning, GAN inversion, scene representations, visual content creation, etc.

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* indicates equal contribution

A diffusion-model based unsupervised framework capable of synthesizing novel views depicting a long camera trajectory flying into an input image.

3D-free unsupervised Single view NeRF-based novel view synthesis via conditional NeRF-GAN training and inversion.