[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74076":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":15,"stars30d":15,"stars90d":15,"forks30d":15,"starsTrendScore":15,"compositeScore":16,"rankGlobal":10,"rankLanguage":10,"license":10,"archived":17,"fork":17,"defaultBranch":18,"hasWiki":19,"hasPages":17,"topics":20,"createdAt":10,"pushedAt":10,"updatedAt":21,"readmeContent":22,"aiSummary":23,"trendingCount":15,"starSnapshotCount":15,"syncStatus":24,"lastSyncTime":25,"discoverSource":26},74076,"EMO","HumanAIGC\u002FEMO","HumanAIGC","Emote Portrait Alive: Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions","",null,7619,931,329,246,0,39.91,false,"main",true,[],"2026-06-12 02:03:21","# EMO\nEmote Portrait Alive: Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions\n\nLinrui Tian, Qi Wang, Bang Zhang, Liefeng Bo,\n\nInstitute for Intelligent Computing, Alibaba Group\n\n\u003Cstrong> at European Conference on Computer Vision (ECCV) 2024 \u003C\u002Fstrong>\n\n\u003Ca href='https:\u002F\u002Fhumanaigc.github.io\u002Femote-portrait-alive\u002F'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FProject-Page-Green'>\u003C\u002Fa>\n\u003Ca href='https:\u002F\u002Farxiv.org\u002Fabs\u002F2402.17485'>\u003Cimg src='https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPaper-Arxiv-red'>\u003C\u002Fa>\n[![YouTube](https:\u002F\u002Fbadges.aleen42.com\u002Fsrc\u002Fyoutube.svg)](https:\u002F\u002Fyoutu.be\u002FVlJ71kzcn9Y)\n\n\n \n## Citation\n```\n@misc{tian2024emo,\n      title={EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions}, \n      author={Linrui Tian and Qi Wang and Bang Zhang and Liefeng Bo},\n      year={2024},\n      eprint={2402.17485},\n      archivePrefix={arXiv},\n      primaryClass={cs.CV}\n}\n```\n\n\n\n\n\n\n\n","EMO项目旨在通过音频到视频的扩散模型在较弱条件下生成具有表现力的人像视频。其核心功能是将输入的音频转换为与之相匹配的表情丰富的动态人像视频，利用了先进的深度学习技术以实现自然流畅的表情变化。该项目特别适用于需要根据声音自动生成相应面部动画的应用场景，如虚拟主播、游戏角色表情制作以及教育娱乐内容创作等领域。",2,"2026-06-11 03:48:41","high_star"]