Is it possible to train a cGAN (Conditional Generative Adversarial Networks) model for monocular depth perception? If the answer is yes, then it would mean that we have a way to allow an artificial system to acquire some basic concept about distance in the physical world, learning from only flat images, starting with nothing. The type of training proposed »
In this report we study the possibility of building the neural model of human faces using cGAN. In my last experiment Generate Photo-realistic Avatars with DCGAN I showed that it is possible to use DCGAN (Deep Convolutional Generative Adversarial Networks), the non-conditional variation of GAN, to synthesize photo-realistic animated facial expressions using a model trained from limited number of »
In this report we explore the feasibility of using DCGAN (Deep Convolutional Generative Adversarial Networks) to generate the neural model of a specific person from limited amount of images or videos, with the aim of creating a controllable avatar with photo-realistic animated expressions out of such a neural model. Here DCGAN holds the promise that the neural model created »
Introduction Our ultimate goal is to generate 3D models out of textual or verbal commands. Here we tackle (for now) the simpler problem of generate 2D images, before moving on the more complex problem of dealing with 3D models. There have been some recent research that are relevant to the generation of 2D images that can also handle lighting, »
This is part 2 of the Holodeck series, focusing on issues related to knowledge representation (KR). This is a followup on the first post Crowd-driven Holodeck, where a skeletal design was presented for a HAI Holodeck. A quick recap To put this post in context (more can be found in the first post: This series discusses a HAI Holodeck, »
You may have seen the Holodeck device that appeared in the TV series Star Trek: The Next Generation, where a user goes into the Holodeck, issues verbal instructions, and entirely realistic 3D objects or environment would appear instantly. This post explores the relevant AI technology needed in order to support such a vision. Here we use the Holodeck as »