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researchmm/MM-Diffusion

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View on GitHub↗
453 stars·24 forks·Python·MIT·1 view

MM Diffusion

[CVPR'23] MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

Features

  • Video Generation - Joint audio and video generation.
  • Generation - Listed in the “Generation” section of the Awesome Diffusion Models awesome list.

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Frequently asked questions

What does researchmm/mm-diffusion do?

[CVPR'23] MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

What are the main features of researchmm/mm-diffusion?

The main features of researchmm/mm-diffusion are: Video Generation, Generation.

What are some open-source alternatives to researchmm/mm-diffusion?

Open-source alternatives to researchmm/mm-diffusion include: mkfmiku/vidm — [AAAI23 Oral] Official implementations of Video Implicit Diffusion Models. voletiv/mcvd-pytorch — Official implementation of MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation… buggyyang/rvd — Diffusion Probabilistic Modeling for Video Generation. johannakarras/dreampose — Official implementation of "DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion". alexiajm/adversarialconsistentscorematching — Code for paper "Adversarial score matching and improved sampling for image generation". ailab-cvc/videocrafter — Videocrafter is a latent diffusion model designed for AI video synthesis. It functions as both a text-to-video and…