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StreamDiffusion: A Pipeline-level Solution for Real-time Interactive Generation

paper: https://arxiv.org/pdf/2312.12491v1.pdf

source code: https://github.com/cumulo-autumn/streamdiffusion?tab=readme-ov-file

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Open-Vocabulary SAM


[Paper] [Project Page] [Hugging Face Demo]

Source Code: https://github.com/harboryuan/ovsam?tab=readme-ov-file



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PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding

[Paper] [Project Page] [Model Card]
[🤗 Demo (Realistic)] [🤗 Demo (Stylization)]

🌠 Key Features:
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Awesome-AIGC-3D

A curated list of awesome AIGC 3D papers, inspired by awesome-NeRF.

Source code: https://github.com/hitcslj/awesome-aigc-3d?tab=readme-ov-file

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EfficientViT - SAM:69x Faster SAM: Multi-Scale Linear Attention for High-Resolution Dense Prediction

1. Channel: @deeplearning_ai

2.Source Code: https://github.com/mit-han-lab/efficientvit

3. Paper: https://arxiv.org/abs/2402.05008

🆔🆔 Magic-Me: Identity-Specific Video 🆔🆔

👉hashtag#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 💙

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel Video Custom Diffusion (VCD) framework
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✅Improvement in aligning IDs-images and text
✅Robust 3D Gaussian Noise Prior for denoising
✅Better Inter-frame correlation / video consistency
✅New modules F-VCD/T-VCD for videos upscale
✅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

👉Channel: @deeplearning_ai
👉Paper https://arxiv.org/pdf/2402.09368.pdf
👉Project https://magic-me-webpage.github.io/
👉Code https://github.com/Zhen-Dong/Magic-Me

🌟 Discover 6DRepNet: The Ultimate Head Pose Estimation Model!

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Watch the performance showcase on GitHub for future advancements.

[Source Code] [Paper]

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