Image Operations with cGAN

In this report we explore the possibility of using cGAN (Conditional Generative Adversarial Networks) for performing automatic graphic operations on the photographs or videos of human faces, similar to those typically done manually using a software tool such as Photoshop or After Effects, by learning from examples. Motivation A good part of my research in Machine Learning has to »

Monocular Depth Perception with cGAN

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 »

Generate Photo-realistic image from sketch using cGAN

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 »

Generate Photo-realistic Avatars with DCGAN

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 »

Image interpolation, extrapolation, and generation

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, »

Word2vec and IPA

Word2vec is an invaluable tool for finding hidden structure in a text corpus. It is essential for the TAI's IPA project, but we will also need to add some refinements over the standard Word2vec in order to meet our needs. This post is part of the TAI thread, which explores how to design and implement the terraAI (a.k. »

Holodeck - Knowledge Representation - part 2

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, »

How to build a Holodeck - part 1

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 »

ML Resources

This post is for cataloging those online resources that are useful to my work for the terraAI project, in particular those related to Machine Learning. Hopefully these will also be useful to other Machine Learning researchers. Typesetting math formulas It would seem that the best way to typeset formulas, which is useful when discussing topics related to Machine Learning, »