A Round Up Of NVIDIA’s GPU Technology Conference (GTC)
Synced Global AI Weekly March 24th
Tag: gan
GTC 2019 | NVIDIA’s New GauGAN Transforms Sketches Into Realistic Images
At the NVIDIA GPU Technology Conference (GTC) which kicked off today, NVIDIA unveiled its latest image processing research effort — GauGAN, a generative adversarial network-based technique capable of transforming segmentation maps into realistic photos.
GTC Preview & NVIDIA AI Research Recap
GTC 2019 runs next Monday through Thursday (March 18 — 21), and while we can only speculate what surprises NVIDIA CEO Jensen Huang might have in store for us, we can get some sense of where the company is headed by looking at what it’s been up to for the last 12 months.
From Faces to Kitties to Apartments: GAN Fakes the World
As Synced previously reported, these hyperrealistic images now flooding the Internet come from US chip giant NVIDIA’s StyleGAN, a generative adversarial network based face generator that performs so well that most people can’t distinguish its creations from photos of real people.
AI Biweekly: Trending StyleGAN Raises Concerns; AI Applications in the Finance Industry
10 AI News You Must Know from February W 1 – W 2
NVIDIA Open-Sources Hyper-Realistic Face Generator StyleGAN
In December Synced reported on a hyperrealistic face generator developed by US chip giant NVIDIA. The GAN-based model performs so well that most people can’t distinguish the faces it generates from real photos. This week NVIDIA announced that it is open-sourcing the nifty tool, which it has dubbed “StyleGAN”.
Tsinghua University Proves Quantum Supremacy on GANs
Many scientists believe that a quantum computing device will one day perform highly complex computational tasks which are far beyond the ability of today’s classical computers.
Never Forget the Power of Government on AI
Subscribe to Synced Global AI Weekly Microsoft Awarded Five-Year $1.76 Billion IDIQ Contract by DoD Microsoft was awarded a $1,760,000,000 indefinite-delivery/indefinite-quantity (IDIQ)Continue Reading
Can AI Judge a Paper on Appearance Alone?
The number of AI-related research papers has skyrocketed in recent years, outpacing papers from all other academic topics since 2000. This has, not unsurprisingly, resulted in a shortage of qualified peer reviewers in the machine learning community, particularly when it comes to conference paper submissions.
White Hats Vs CAPTCHAs
Text-based CAPTCHA remain one of the most visible and commonly used mechanisms for website security. As a sort of online gatekeeper that distinguishes between humans and bots, the little solvable image fields have critical commercial applications in blocking automatic spam and preventing e-transfer fraud; and can also stop bots from spreading fraudulent information, etc.
AI Brush: New GAN Tool Paints Worlds
The digital painting tool GANpaint has gone viral on social media. The product of a team of high-profile researchers from MIT, IBM, Google, and the Chinese University of Hong Kong, GAPpaint allows anyone — even those with little knowledge of digital painting or photoshop — to “paint” incredibly complex and detailed photorealistic scenes.
DeNA’s PSGAN Dresses Anime Characters at 1024×1024 Pixels
Founded in 1999, Tokyo-based DeNA has developed popular platforms and services for gaming, E-commerce, automotive, healthcare and entertainment content distribution. As AI continues transforming all things digital, DeNA is expanding its deep learning tech capabilities to support R&D on new techniques.
Georgia Tech & Google Brain’s GAN Lab Visualizes Model Training in Browsers
Georgia Tech and Google Brain researchers have introduced the new interactive tool GAN Lab, which visually presents the training process of complex machine learning model Generative Adversarial Networks (GANs). Even machine learning newbs can now experiment with GAN models using only a common web browser.
Durham University’s GANomaly Improves Anomaly Detection
In a new paper Durham University researchers introduce a anomaly detection model, GANomaly, comprising a conditional generative adversarial network that “jointly learns the generation of high-dimensional image space and the inference of latent space.” The process enables the model to perform anomaly detection tasks even in sample-poor environments.
Bottle into Basket: Realistic Object Composition with AI
Compositing multiple objects from different sources into one image is a formidable computer graphics challenge involving relative scaling, spatial layout, occlusion, and viewpoint transformation of objects from the 3D world to a 2D image.
Silicon Night Fever: Berkeley AI Gets Down
Electrifying an entire dance club is easy if you have killer moves like John Travolta in Saturday Night Fever. But for the rest of us, not so much. We may shake our butts and swing our arms, but let’s face it: some people just can’t dance. But now there’s hope, thanks to AI.
Google Brain Plays Games With GANs
A Google Brain research group has published a paper proposing a new method for evaluating generative models by using insights from competitive games between human players.
AI Abuzz over CycleGan Face Swapping Video
YouTuber “TJWei” recently uploaded a “Face-off” video on YouTube. The four-minute split-screen clip sees two figures speaking and emoting simultaneously. Both look human, but one is an entity generated in real-time by an AI algorithm.
CVPR 2017: The Fusion of Deep Learning and Computer Vision, What’s Next?
CVPR 2017 conference covered topics in: Machine Learning, Object Recognition & Scene Understanding – Computer Vision & Language, 3D Vision, Human Analyzing, Low- & Mid- Level Vision, Image Motion & Tracking: Video Analysis, Computational Photography, Applications.
PixelGAN Autoencoders
PixelGAN is an autoencoder for which the generative path is a convolutional autoregressive neural network on pixels, conditioned on a latent code, and the recognition path uses a generative adversarial network (GAN) to impose a prior distribution on the latent code.