Objects generated by 3D-GAN from vectors, without a reference image/object. We show, for the last two objects in each row, the nearest neighbor retrieved from the training set. We see that the generated objects are similar, but not identical, to examples in the training set. For comparison, we show objects generated by the previous state-of-the-art [Wu et al., 2015] (results supplied by the authors). We also show objects generated by autoencoders trained on a single object category, with latent vectors sampled from empirical distribution. See paper Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling.

Radical Reads: Generative AI and the Evolution of Ideas

An idea, of course, is the domain of the human mind. Breakthrough advances in generative AI technology, however, are changing the notion of what it means to substantiate an idea, offering new mechanisms for creation and iteration that were – until just recently – entirely bound by our biological capacity…

Read More »

© 2022 Radical Ventures Investments Inc.