Researchers at Washington State University (WSU) unveiled a new AI-guided 3D printing technique that can help physicians print intricate replicas of human organs. Surgeons can then use these organ models to practice before performing the actual surgery, which gives doctors more tools to improve surgical results. The AI algorithm was trained on images and key attributes of human kidneys and��
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This post was updated January 16, 2024. Recent years have witnessed a massive increase in the volume of 3D geospatial data being generated. This data provides rich real-world environmental and contextual information, spatial relationships, and real-time monitoring capabilities for industrial applications. It can enhance the realism, accuracy, and effectiveness of simulations across various��
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Reconstructing a smooth surface from a point cloud is a fundamental step in creating digital twins of real-world objects and scenes. Algorithms for surface reconstruction appear in various applications, such as industrial simulation, video game development, architectural design, medical imaging, and robotics. Neural Kernel Surface Reconstruction (NKSR) is the new NVIDIA algorithm for��
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A new model generates 3D reconstructions using neural networks, turns 2D video clips into detailed 3D structures �� generating lifelike virtual replicas of buildings, sculptures and other real-world objects.
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Robots are increasing in complexity, with a higher degree of autonomy, a greater number and diversity of sensors, and more sensor fusion-based algorithms. Hardware acceleration is essential to run these increasingly complex workloads, enabling robotics applications that can run larger workloads with more speed and power efficiency. The mission of NVIDIA Isaac ROS has always been to empower��
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Research on neural fields has been an increasingly hot topic in computer graphics and computer vision in recent years. Neural fields can represent 3D data like shape, appearance, motion, and other physical quantities by using a neural network that takes coordinates as input and outputs the corresponding data at that location. These representations have been proven to be useful in various��
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The new NVIDIA NGP Instant NeRF is a great introduction to getting started with neural radiance fields. In as little as an hour, you can compile the codebase, prepare your images, and train your first NeRF. Unlike other NeRF implementations, Instant NeRF only takes a few minutes to train a great-looking visual. In my hands-on video (embedded), I walk you through the ins and outs of making��
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Instance segmentation is a core visual recognition problem for detecting and segmenting objects. In the past several years, this area has been one of the holy grails in the computer vision community with wide applications ranging from autonomous vehicles (AV), robotics, video analysis, smart home, digital human, and healthcare. Annotation, the process of classifying every object in an image��
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This post discusses tensor methods, how they are used in NVIDIA, and how they are central to the next generation of AI algorithms. Tensors, which generalize matrices to more than two dimensions, are everywhere in modern machine learning. From deep neural networks features to videos or fMRI data, the structure in these higher-order tensors is often crucial.
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Research efforts in 3D computer vision and AI have been rising side-by-side like two skyscrapers. But the trip between these formidable towers has involved clambering up and down dozens of stairwells. To bridge that divide, NVIDIA recently released Kaolin, which in a few steps moves 3D models into the realm of neural networks. Implemented as a PyTorch library, Kaolin can slash the job of��
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