Étiquette : nvidia (Page 1 of 2)

“Harness the power of AI to quickly turn simple brushstrokes into realistic landscape images for backgrounds, concept exploration, or creative inspiration. 🖌️ The NVIDIA Canvas app lets you create as quickly as you can imagine.”

via NVIDIA Studio

“We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis. The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and also better disentangles the latent factors of variation. To quantify interpolation quality and disentanglement, we propose two new, automated methods that are applicable to any generator architecture. Finally, we introduce a new, highly varied and high-quality dataset of human faces.”

via Tero Karras FI (YouTube)

“Powered by the Quadro RTX 6000, this demo shows off production-quality rendering and cinematic frame rates, enabling users to interact with scene elements in real time”.

via NVIDIA (YouTube)

“Einride isn’t the only outfit trying to ditch the human driver along with the diesel. But where Tesla, Volvo, Daimler, and Uber are looking to free up some space in the cab, Einride has done away with it altogether. Instead, its trucks carry a suite of lidar, radar, and camera sensors, feeding information about the environment to Nvidia’s AI supercomputer”.

Source : Einride’s T-log Is a Self-Driving Truck Made for the Forest | WIRED

«Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains. Since there exists an infinite set of joint distributions that can arrive the given marginal distributions, one could infer nothing about the joint distribution from the marginal distributions without additional assumptions».

Source : Unsupervised Image-to-Image Translation Networks | Research

The trunk of a self-driving Ford Fusion

«Everything the vehicle “sees” with its sensors, all of the images, mapping data, and audio material picked up by its cameras, needs to be processed by giant PCs in order for the vehicle to make split-second decisions. All this processing must be done with multiple levels of redundancy to ensure the highest level of safety. This is why so many self-driving operators prefer SUVs, minivans, and other large wheelbase vehicles: autonomous cars need enormous space in the trunk for their big “brains.”. But Nvidia claims to have shrunk down its GPU, making it an easier fit for production vehicles».

Source : Nvidia says its new supercomputer will enable the highest level of automated driving – The Verge

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