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pro vyhledávání: '"He, Huiguo"'
Autor:
He, Huiguo, Yang, Huan, Tuo, Zixi, Zhou, Yuan, Wang, Qiuyue, Zhang, Yuhang, Liu, Zeyu, Huang, Wenhao, Chao, Hongyang, Yin, Jian
Story visualization aims to create visually compelling images or videos corresponding to textual narratives. Despite recent advances in diffusion models yielding promising results, existing methods still struggle to create a coherent sequence of subj
Externí odkaz:
http://arxiv.org/abs/2407.12899
Autor:
Zhu, Junchen, Yang, Huan, Wang, Wenjing, He, Huiguo, Tuo, Zixi, Yu, Yongsheng, Cheng, Wen-Huang, Gao, Lianli, Song, Jingkuan, Fu, Jianlong, Luo, Jiebo
Videos for mobile devices become the most popular access to share and acquire information recently. For the convenience of users' creation, in this paper, we present a system, namely MobileVidFactory, to automatically generate vertical mobile videos
Externí odkaz:
http://arxiv.org/abs/2307.16371
Autor:
He, Huiguo, Wang, Tianfu, Yang, Huan, Fu, Jianlong, Yuan, Nicholas Jing, Yin, Jian, Chao, Hongyang, Zhang, Qi
We study the task of generating profitable Non-Fungible Token (NFT) images from user-input texts. Recent advances in diffusion models have shown great potential for image generation. However, existing works can fall short in generating visually-pleas
Externí odkaz:
http://arxiv.org/abs/2306.11731
Autor:
Zhu, Junchen, Yang, Huan, He, Huiguo, Wang, Wenjing, Tuo, Zixi, Cheng, Wen-Huang, Gao, Lianli, Song, Jingkuan, Fu, Jianlong
In this paper, we present MovieFactory, a powerful framework to generate cinematic-picture (3072$\times$1280), film-style (multi-scene), and multi-modality (sounding) movies on the demand of natural languages. As the first fully automated movie gener
Externí odkaz:
http://arxiv.org/abs/2306.07257
With the explosive popularity of AI-generated content (AIGC), video generation has recently received a lot of attention. Generating videos guided by text instructions poses significant challenges, such as modeling the complex relationship between spa
Externí odkaz:
http://arxiv.org/abs/2305.10874
Autor:
Ruan, Ludan, Ma, Yiyang, Yang, Huan, He, Huiguo, Liu, Bei, Fu, Jianlong, Yuan, Nicholas Jing, Jin, Qin, Guo, Baining
We propose the first joint audio-video generation framework that brings engaging watching and listening experiences simultaneously, towards high-quality realistic videos. To generate joint audio-video pairs, we propose a novel Multi-Modal Diffusion m
Externí odkaz:
http://arxiv.org/abs/2212.09478
Publikováno v:
In Neurocomputing 28 August 2022 501:75-87
We present VideoFactory, an innovative framework for generating high-quality open-domain videos. VideoFactory excels in producing high-definition (1376x768), widescreen (16:9) videos without watermarks, creating an engaging user experience. Generatin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b47b069c65ba1449f410ea4525802b56
http://arxiv.org/abs/2305.10874
http://arxiv.org/abs/2305.10874
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