Chengkai Zhang

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Humans demonstrate remarkable abilities to predict physical events in complex scenes. Two classes of models for physical scene understanding have recently been proposed: " Intuitive Physics Engines " , or IPEs, which posit that people make predictions by running approximate probabilistic simulations in causal mental models similar in nature to video-game(More)
We study the problem of 3D object generation. We propose a novel framework, namely 3D Generative Adversarial Network (3D-GAN), which generates 3D objects from a probabilistic space by leveraging recent advances in volumetric convo-lutional networks and generative adversarial nets. The benefits of our model are threefold: first, the use of an adversarial(More)
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