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title
Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
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Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
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2026-03-07 23:49:50
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Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation Vikram Voleti *, Alexia Jolicoeur-Martineau *, Christopher Pal Code , Paper , Blog Summary General purpose model for video generation, forward/backward prediction, and interpolation Uses a score-based diffusion loss function to generate novel frames Injects Gaussian noise into the current frames and denoises them conditional on past and/or future frames Randomly masks past and/or future frames during training which allows the model to handle the four cases: Unconditional Generation : both past and future are unknown Future Prediction : only the past is known Past Reconstruction : only the future is known Interpolation : both past and present are known Uses a 2D convolutional U-Net instead of a complex 3D or recurrent or transformer architecture Conditions on past and future...
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