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20212023
most citedLAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

34 citations · 91 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023★ 34 cited

LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Yaohui Wang, Xinyuan Chen, Xin Ma +17

This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challengi…

cs.CV2023★ 32 cited

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Yi Wang, Yinan He, Yizhuo Li +13

This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodal understand…

cs.CV2023

Weakly Supervised Scene Text Generation for Low-resource Languages

Yangchen Xie, Xinyuan Chen, Hongjian Zhan +4

A large number of annotated training images is crucial for training successful scene text recognition models. However, collecting sufficient datasets can be a labor-intensive and c…

cs.SD2023★ 3 cited

Long-Term Rhythmic Video Soundtracker

Jiashuo Yu, Yaohui Wang, Xinyuan Chen +2

We consider the problem of generating musical soundtracks in sync with rhythmic visual cues. Most existing works rely on pre-defined music representations, leading to the incompete…

cs.CV2023★ 5 cited

LEO: Generative Latent Image Animator for Human Video Synthesis

Yaohui Wang, Xin Ma, Xinyuan Chen +4

Spatio-temporal coherency is a major challenge in synthesizing high quality videos, particularly in synthesizing human videos that contain rich global and local deformations. To re…

cs.CV2023

Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation

Zeyu Lu, Chengyue Wu, Xinyuan Chen +4

Diffusion models have attained impressive visual quality for image synthesis. However, how to interpret and manipulate the latent space of diffusion models has not been extensively…