3DIS or Trainable 3D Interaction Spaces is a cutting-edge technology that models the recognition of multiple triplets in one frame. This technology is key in creating digital interactions that closely resemble human interactions, making it possible for humans to interact with machines and robots more naturally.
What is 3DIS?
Imagine being able to interact with your computer, tablet or phone using gestures that feel natural to you. 3DIS technology enables this by creating an interaction space
A 3D Dynamic Scene Graph, or DSG, is a powerful tool used in various fields such as computer graphics, robotics, and virtual reality. It is a representation that captures both the spatial and temporal aspects of a dynamic environment. This multi-layered graph is made up of nodes and edges that hold important information about the environment it represents.
Understanding the Concept of a 3D Dynamic Scene Graph
The world is constantly changing, and it is important to have a tool that can repres
The DeltaConv algorithm is an innovative method for improving convolutional neural networks (CNNs) for use on curved surfaces. In traditional CNNs, anisotropic convolution is a foundational aspect, but the process of transferring that same concept to surfaces presents significant challenges. DeltaConv seeks to solve that problem by using vector calculus, which is a more natural fit for working with curved surfaces. The resulting convolution operator is both simple and robust, providing state-of-
What is GMI?
GMI, also known as Graphic Mutual Information, is a measurement method used to determine the correlation between input graphs and high-level hidden representations. Different from the conventional mutual information computations that take place in vector space, GMI extends the calculation to the graph domain. Measuring mutual information from two aspects of node features and topological structure is essential in the graph domain, and GMI makes that possible.
Benefits
GMI provide
What is imGHUM?
imGHUM is a computer program that generates 3D models of human bodies and their movements. The models are represented as a function that measures the distance between a point in space and the surface of the human body.
How Does imGHUM Work?
imGHUM creates the 3D model of a human body by using a generative latent code, which is a set of parameters that determine the shape, size, and positioning of the different body parts. The program then computes the distance from each point
Overview of Models Genesis: A Self-Supervised Approach for Learning 3D Image Representations
If you are interested in the field of medical imaging, you might have heard of a new technique called Models Genesis, or Generic Autodidactic Models. This technique is used for learning 3D image representations, and it has the potential to revolutionize the way we analyze medical images.
The idea behind Models Genesis is to learn a common image representation that can be used across diseases, organs, a
What is NeRF?
NeRF, short for Neural Radiance Fields, is a scientific concept that represents a scene with learned, continuous volumetric radiance field $F_\theta$ defined over a bounded 3D volume. It is a new technology that allows for the creation of extremely realistic 3D models with exceptionally high levels of detail.
How NeRF Works
In a NeRF, $F_\theta$ is a multilayer perceptron (MLP) that takes as input a 3D position $x = (x, y, z)$ and unit-norm viewing direction $d = (dx, dy, dz)$,
Introducing PointNet: A Revolutionary Architecture for Object Classification and Semantic Parsing
If you're interested in the world of machine learning, then you've probably heard of PointNet. PointNet is a revolutionary architecture that has been gaining a lot of traction lately in the field of deep learning. It takes point clouds as input and outputs class labels for entire inputs or per point segment/part labels for each point of the input. But what exactly is PointNet and how does it work?