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A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models. [2]
Make-A-Video (2022) is a text-to-video diffusion model. [74] [75] CM3leon (2023) is not a diffusion model, but an autoregressive causally masked Transformer, with mostly the same architecture as LLaMa-2. [76] [77] Transfusion architectural diagram. Transfusion (2024) is a Transformer that combines autoregressive text generation and denoising ...
A video generated by Sora of someone lying in a bed with a cat on it, containing several mistakes. The technology behind Sora is an adaptation of the technology behind DALL-E 3. According to OpenAI, Sora is a diffusion transformer [10] – a denoising latent diffusion model with one Transformer as the denoiser. A video is generated in latent ...
The model was released in February 2023. The Gen-1 model was trained and developed by Runway based on the original paper Structure and Content-Guided Video Synthesis with Diffusion Models from Runway Research. [30] Gen-1 is an example of generative artificial intelligence for video creation.
Dream Machine is a text-to-video model created by the San Francisco-based generative artificial intelligence company Luma Labs, which had previously created Genie, a 3D model generator. It was released to the public on June 12, 2024, which was announced by the company in a post on X alongside examples of videos it created. [1]
The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [ 3 ] Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian ) on training images.
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Example of six evidence accumulation sequences from an unbiased (100% noise) source. The dotted lines indicate the thresholds for decision making for each of the two alternatives. The drift-diffusion model (DDM) is a well defined [19] model, that is proposed to implement an optimal decision policy for 2AFC. [20]