Polygon MeshA 3D representation consisting of vertices, edges, and faces (typically triangles or quads) that define the surface of a 3D object. Meshes are the standard representation in computer graphics and can efficiently represent complex surfaces with varying levels of detail.
VoxelA volumetric pixel - the 3D equivalent of a 2D pixel. Voxel representations divide 3D space into a regular grid of cubic cells, each storing properties like occupancy or color. Simple to process but memory-intensive at high resolutions.
UV MappingThe process of projecting a 2D image texture onto a 3D model's surface. UV coordinates (U and V are the axes of the 2D texture) define how each point on the 3D surface maps to a point on the 2D texture image.
Normal VectorA vector perpendicular to a surface at a given point. Surface normals are essential for lighting calculations, collision detection, and understanding surface orientation in 3D geometry.
Depth MapA 2D image where each pixel value represents the distance from the camera to the corresponding point in the scene. Depth maps bridge 2D images and 3D geometry and can be captured by RGB-D cameras or estimated from standard images.
Volumetric RenderingA technique for rendering 3D data by casting rays through a volume and accumulating color and opacity values along each ray. Used by NeRF and other neural rendering methods to generate images from learned 3D representations.
Signed Distance Function (SDF)A mathematical function that returns the shortest distance from any point in space to the nearest surface, with the sign indicating whether the point is inside (negative) or outside (positive) the object. SDFs provide a powerful implicit representation for 3D shapes.
Multi-View ReconstructionThe process of reconstructing a 3D model from multiple 2D photographs taken from different viewpoints. Techniques range from classical Structure-from-Motion to modern neural methods like NeRF.
CAD ModelComputer-Aided Design model - a precise mathematical representation of a 3D object created using design software. CAD models use parametric surfaces and solid geometry, offering exact specifications used in engineering and manufacturing.
TextureA 2D image applied to the surface of a 3D model to add visual detail such as color, patterns, or surface properties like roughness and reflectivity, without increasing geometric complexity.
LiDARLight Detection and Ranging - a remote sensing technology that measures distances by illuminating a target with laser light and measuring the reflected pulses. LiDAR produces high-resolution point clouds of real-world environments.
Implicit Neural RepresentationA method of representing 3D shapes or scenes as continuous functions parameterized by neural networks, rather than as discrete data structures like meshes or voxels. The network learns to map coordinates to properties like occupancy or color.
Shape EmbeddingA compact vector representation of a 3D shape in a learned feature space, capturing the essential geometric and semantic properties of the object. Shape embeddings enable similarity search, classification, and generation of 3D objects.
Gaussian SplattingA 3D scene representation technique that models a scene as a collection of 3D Gaussian primitives, each with position, covariance, opacity, and color. It enables real-time, high-quality rendering of complex scenes through efficient rasterization.
PhotogrammetryThe science of making measurements from photographs to reconstruct 3D models of real-world objects or environments. Modern photogrammetry uses computer vision algorithms to automatically match features across images and triangulate 3D positions.
Marching CubesAn algorithm for extracting a polygonal mesh surface from a three-dimensional scalar field (such as a signed distance function or voxel grid). It processes the field cube by cube, determining which edges the surface crosses and generating triangles accordingly.
SketchfabA major online platform for publishing, sharing, and discovering 3D, VR, and AR content. Objaverse was primarily sourced from Sketchfab, which hosts millions of 3D models uploaded by artists, designers, and 3D scanning enthusiasts.
Ray CastingA technique for determining which objects in a 3D scene are visible by tracing rays from the camera through each pixel into the scene. Ray casting is used in NeRF and volumetric rendering to sample density and color along each ray path.
Text-to-3D GenerationThe task of creating a 3D object or scene from a natural language text description. Methods like DreamFusion, Magic3D, and Point-E use combinations of text-conditioned diffusion models and 3D representations to generate 3D content from text prompts.
Occupancy NetworkA neural implicit representation that maps a 3D coordinate to an occupancy probability (whether the point is inside or outside an object). Occupancy networks can represent complex shapes with arbitrary resolution without requiring discrete voxel grids.
Shape CompletionThe task of predicting the complete 3D shape of an object from a partial observation, such as a single depth scan or a partial point cloud. Deep learning models trained on 3D datasets like Objaverse and ShapeNet can learn to infer missing geometry.
PointNetA pioneering deep learning architecture designed to directly process unordered point cloud data. PointNet uses shared multi-layer perceptrons and a symmetric max-pooling operation to achieve permutation invariance, enabling 3D classification and segmentation directly from point sets.
Mesh DecimationThe process of reducing the number of polygons in a 3D mesh while preserving its overall shape and visual appearance. This is important for optimizing 3D models for real-time rendering, web display, and efficient storage in large-scale datasets.
Objaverse-XLAn expanded version of Objaverse containing over 10 million 3D objects sourced from multiple platforms including Sketchfab, Thingiverse, GitHub, and the Smithsonian, making it the largest open 3D dataset.
DreamFusionA text-to-3D generation method by Google that uses a pre-trained text-to-image diffusion model to optimize a NeRF representation, enabling 3D object creation from text descriptions without 3D training data.
Zero-1-to-3A method for generating novel views of an object from a single image, trained on Objaverse data, enabling 3D reconstruction from just one photograph.
ShapeNetA richly-annotated, large-scale dataset of 3D shapes containing 51,300 unique 3D models covering 55 common object categories, widely used as a benchmark in 3D deep learning research.
Triplane RepresentationA compact 3D representation that encodes a 3D scene using three orthogonal feature planes (XY, XZ, YZ), enabling efficient 3D generation and rendering with 2D neural network backbones.
Multi-View StereoA technique for reconstructing 3D geometry from multiple overlapping photographs by finding corresponding points across views and triangulating their 3D positions.
Mesh SimplificationAlgorithms that reduce the polygon count of a 3D mesh while preserving its visual appearance, important for efficient storage and rendering of large-scale 3D datasets.
Cap3DA method for automatically generating detailed text descriptions (captions) for 3D objects in Objaverse, enabling text-based search and text-to-3D generation training.
Point-EAn OpenAI model that generates 3D point clouds from text descriptions, trained on a large dataset of text-3D pairs, enabling rapid 3D content creation from natural language.
Radiance FieldA continuous function that maps 3D coordinates and viewing directions to color and density values, representing a scene's appearance from any viewpoint. NeRF is the most well-known implementation.
Digital TwinA virtual replica of a physical object, process, or system that is updated in real-time with sensor data. 3D datasets like Objaverse help create more realistic and diverse digital twins.
Implicit SurfaceA 3D surface defined as the zero-level set of a continuous function, rather than by explicit vertices and faces. Neural implicit surfaces like DeepSDF and occupancy networks fall in this category.
3D ReconstructionThe process of creating a 3D model from 2D observations such as photographs, depth maps, or sensor data. Methods range from classical structure-from-motion to modern neural reconstruction techniques.
View SynthesisGenerating novel views of a scene from viewpoints that were not captured by cameras. NeRF and Gaussian Splatting excel at this task by learning continuous 3D scene representations.
Texture SynthesisAutomatically generating texture images for 3D surfaces, either by extending sample textures or using AI to create textures from text descriptions. Important for realistic rendering of generated 3D objects.
Watertight MeshA polygon mesh that forms a complete, closed surface without holes or gaps. Watertight meshes are required for many operations like 3D printing, boolean operations, and inside/outside queries.
Level of Detail (LOD)A technique for managing complexity by using different mesh resolutions depending on the viewing distance. Objects far from the camera use simplified meshes, while nearby objects use high-detail versions.
Scene GraphA structured representation of a 3D scene describing objects, their attributes (color, material, shape), and relationships (on top of, next to, inside). Scene graphs enable semantic understanding and generation of 3D environments.
Neural Signed Distance FunctionA neural network trained to output the signed distance from any 3D point to the nearest surface, providing a continuous and differentiable implicit representation of 3D shapes.
NeRF in the WildAn extension of NeRF that handles unconstrained photo collections with varying lighting, exposure, and transient occluders, enabling 3D reconstruction from tourist photographs.