March 5, 2024, 2:49 p.m. | Litong Gong, Yiran Zhu, Weijie Li, Xiaoyang Kang, Biao Wang, Tiezheng Ge, Bo Zheng

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.01800v1 Announce Type: new
Abstract: Recently, video generation has achieved significant rapid development based on superior text-to-image generation techniques. In this work, we propose a high fidelity framework for image-to-video generation, named AtomoVideo. Based on multi-granularity image injection, we achieve higher fidelity of the generated video to the given image. In addition, thanks to high quality datasets and training strategies, we achieve greater motion intensity while maintaining superior temporal consistency and stability. Our architecture extends flexibly to the video frame …

arxiv cs.cv fidelity image image-to-video type video video generation

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