Jan. 31, 2024, 4:43 p.m. | Xun Guo, Mingwu Zheng, Liang Hou, Yuan Gao, Yufan Deng, Pengfei Wan, Di Zhang, Yufan Liu, Weiming Hu, Zhengjun Zha, Haibin Huang, Chongyang Ma

cs.CV updates on arXiv.org arxiv.org

Text-guided image-to-video (I2V) generation aims to generate a coherent video
that preserves the identity of the input image and semantically aligns with the
input prompt. Existing methods typically augment pretrained text-to-video (T2V)
models by either concatenating the image with noised video frames channel-wise
before being fed into the model or injecting the image embedding produced by
pretrained image encoders in cross-attention modules. However, the former
approach often necessitates altering the fundamental weights of pretrained T2V
models, thus restricting the model's …

arxiv cs.cv diffusion diffusion models fed general generate identity image image-to-video prompt text text-to-video video wise

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