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Latent Space

Definition

The compressed, lower-dimensional representation of data learned by a neural network's internal layers. Generative models sample from or navigate this space to produce new outputs; its statistical properties differ measurably from the space occupied by authentic photographs.

Related terms

Diffusion Model
A generative neural network architecture (Ho et al., 2020; Stable Diffusion, Rombach et al., 2022) that learns to reverse a noise-addition process...
Autoencoder
A neural network that compresses an input into a compact latent representation (encoder) then reconstructs it (decoder). Face-swap pipelines train autoencoders with...
Blending Mask
In face-swap pipelines, a pixel-level mask that defines the face region to be composited onto the target frame. Imperfect masks leave boundary...
Checkerboard Artifact
A grid-like pattern visible in the Fourier power spectrum of GAN outputs, caused by transposed convolution or bilinear-upsampling operations used to increase...
Encoder-Decoder
A neural architecture where an encoder compresses an input into a compact latent representation and a decoder reconstructs an output image from...
GAN
Generative Adversarial Network. A framework with two neural networks, a generator that creates synthetic data and a discriminator that tries to distinguish...
Generative Adversarial Network (GAN)
A machine learning architecture consisting of two networks trained simultaneously: a generator that produces synthetic images and a discriminator that classifies images...
NeRF (Neural Radiance Field)
A neural representation that encodes a 3-D scene as a continuous volumetric function, allowing novel viewpoints to be rendered. In talking-head systems,...
Voice Conversion
A signal-processing or deep-learning technique that transforms the vocal characteristics of a source speaker's utterance to match a target speaker, while preserving...

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