Key concepts in computer vision, 3D AI, and MLOps — explained by the engineers who build with them.
Computer vision is a field of artificial intelligence that trains machines to interpret and understand visual information from cameras, images, and video — enabling automated detection, tracking, segmentation, and scene understanding.
Read More →3D generative AI uses deep learning models to automatically create three-dimensional assets — meshes, textures, and scenes — from text prompts, images, or other conditioning inputs, dramatically accelerating 3D content workflows.
Read More →Gaussian splatting is a real-time 3D scene representation that models a scene as millions of small 3D Gaussian primitives, each with a position, covariance, colour, and opacity — enabling photorealistic rendering at interactive frame rates without neural network inference.
Read More →A Neural Radiance Field (NeRF) is a neural network that learns a continuous volumetric scene representation from a set of posed images, mapping every 3D position and viewing direction to a colour and density — enabling photorealistic novel-view synthesis.
Read More →A point cloud is an unstructured set of 3D points — each defined by (x, y, z) coordinates and optionally colour, intensity, or normals — captured by LiDAR sensors, depth cameras, or photogrammetry, serving as a raw spatial representation of a physical scene or object.
Read More →Object detection is a computer vision task that identifies and localises objects within an image or video frame by predicting bounding boxes and class labels — enabling machines to understand what objects are present and where they are.
Read More →Retopology is the process of rebuilding the surface mesh of a 3D model with cleaner, more efficient polygon topology — converting dense, irregular scans or sculpts into production-ready meshes with proper edge flow, UVs, and controllable polygon count.
Read More →MLOps (Machine Learning Operations) is the set of practices, tools, and infrastructure for deploying, monitoring, and maintaining machine learning models in production — bridging the gap between model development and reliable, scalable operation.
Read More →A digital twin is a virtual replica of a physical object, environment, or system — continuously synchronised with real-world data — used for monitoring, simulation, analysis, and decision-making across its lifecycle.
Read More →LiDAR (Light Detection and Ranging) is a remote sensing technology that measures distances by emitting laser pulses and recording their return time — producing dense, accurate 3D point clouds of the surrounding environment.
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