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Post #1151
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๐๐ Magic-Me: Identity-Specific Video ๐๐
๐hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel Video Custom Diffusion (VCD) framework
โ High-Quality ID-specific videos generation
โ Improvement in aligning IDs-images and text
โ Robust 3D Gaussian Noise Prior for denoising
โ Better Inter-frame correlation / video consistency
โ New modules F-VCD/T-VCD for videos upscale
โ New train with masked loss by prompt-to-segmentation
hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
๐Channel: @deeplearning_ai
๐Paper https://arxiv.org/pdf/2402.09368.pdf
๐Project https://magic-me-webpage.github.io/
๐Code https://github.com/Zhen-Dong/Magic-Me
๐hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel Video Custom Diffusion (VCD) framework
โ High-Quality ID-specific videos generation
โ Improvement in aligning IDs-images and text
โ Robust 3D Gaussian Noise Prior for denoising
โ Better Inter-frame correlation / video consistency
โ New modules F-VCD/T-VCD for videos upscale
โ New train with masked loss by prompt-to-segmentation
hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
๐Channel: @deeplearning_ai
๐Paper https://arxiv.org/pdf/2402.09368.pdf
๐Project https://magic-me-webpage.github.io/
๐Code https://github.com/Zhen-Dong/Magic-Me
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