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Depth Estimation(also: Monocular Depth Estimation, Depth Prediction)

The computer vision task of predicting the distance from the camera to each point in a scene, producing a depth map in which each pixel carries a distance value. Monocular depth estimation uses a single RGB image (no stereo cameras or LiDAR) and typically relies on deep learning…

Diffusion Model(also: Diffusion-based Generator, Denoising Diffusion Model)

A diffusion model is a class of generative AI that learns to produce images or videos by iteratively denoising a random noise input, reversing a forward process that gradually adds noise to training data. In accessibility work, diffusion models are used to synthesize sign…

Dimensionality Reduction(also: Dimension Reduction, UMAP, t-SNE)

Dimensionality reduction is a class of machine learning techniques that transform high-dimensional data — such as the vector embeddings produced by neural networks — into lower-dimensional representations (typically 2D or 3D) that can be visualised and explored by humans. Common…

Disability-First Dataset(also: Disability-first AI dataset)

An approach to AI dataset creation, articulated by Theodorou et al. and others, that treats serving a disability community as the primary objective rather than collecting disability data as a minority slice of a general-purpose dataset. Examples include VizWiz (blind…

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