3260 papers • 126 benchmarks • 313 datasets
Generate temporal sequences of human motions guided by different signals, e.g., textual descriptions, showing smooth, plausible, and realistic transitions.
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This work introduces FlowMDM, the first diffusion-based model that generates seamless Human Motion Compositions (HMC) without any postprocessing or redundant denoising steps, and introduces the Blended Positional Encodings, a technique that leverages both absolute and relative positional encodings in the denoising chain.
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