title: VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
summary: Video generation has increasingly gained interest in both academia and
  industry. Although commercial tools can generate plausible videos, there is a
  limited number of open-source models available for researchers and engineers.
  In this work, we introduce two diffusion models for high-quality video
  generation, namely text-to-video (T2V) and image-to-video (I2V) models. T2V
  models synthesize a video based on a given text input, while I2V models
  incorporate an additional image input. Our proposed T2V model can generate
  realistic and cinematic-quality videos with a resolution of 1024 times 576,
  outperforming other open-source T2V models in terms of quality. The I2V model
  is designed to produce videos that strictly adhere to the content of the
  provided reference image, preserving its content, structure, and style. This
  model is the first open-source I2V foundation model capable of transforming a
  given image into a video clip while maintaining content preservation
  constraints. We believe that these open-source video generation models will
  contribute significantly to the technological advancements within the
  community.
paper_authors._id: 654094611c4b203c01300dd6
paper_authors.name: Haoxin Chen
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paper_authors.fullname: Haoxin Chen
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paper_authors.name: Menghan Xia
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paper_authors.fullname: Richard
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paper_authors.user: menghanxia
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paper_authors.name: Yingqing He
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paper_authors.fullname: He
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paper_authors.user: Yingqing
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paper_authors.name: Yong Zhang
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paper_authors.name: Xiaodong Cun
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paper_authors.fullname: Xiaodong Cun
paper_authors.type: user
paper_authors.user: vinthony
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paper_authors.name: Shaoshu Yang
paper_authors._id: 654094611c4b203c01300ddc
paper_authors.name: Jinbo Xing
paper_authors.status: admin_assigned
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paper_authors.fullname: Jinbo Xing
paper_authors.type: user
paper_authors.user: Doubiiu
paper_authors._id: 654094611c4b203c01300ddd
paper_authors.name: Yaofang Liu
paper_authors.status: claimed_verified
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paper_authors._id: 658d46649a1397992a4d657f
paper_authors.avatarUrl: /avatars/66d23095b8d0368ea862778dbf123a67.svg
paper_authors.fullname: Raphael Liu
paper_authors.type: user
paper_authors.user: RaphaelLiu
paper_authors._id: 654094611c4b203c01300dde
paper_authors.name: Qifeng Chen
paper_authors.status: admin_assigned
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paper_authors.fullname: Qifeng Chen
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paper_authors.user: cqf
paper_authors._id: 654094611c4b203c01300ddf
paper_authors.name: Xintao Wang
paper_authors.status: admin_assigned
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paper_authors.fullname: Xintao Wang
paper_authors.type: user
paper_authors.user: Xintao
paper_authors._id: 654094611c4b203c01300de0
paper_authors.name: Chao Weng
paper_authors._id: 654094611c4b203c01300de1
paper_authors.name: Ying Shan
paper_title: VideoCrafter1: Open Diffusion Models for High-Quality Video Generation
paper_summary: Video generation has increasingly gained interest in both academia and
  industry. Although commercial tools can generate plausible videos, there is a
  limited number of open-source models available for researchers and engineers.
  In this work, we introduce two diffusion models for high-quality video
  generation, namely text-to-video (T2V) and image-to-video (I2V) models. T2V
  models synthesize a video based on a given text input, while I2V models
  incorporate an additional image input. Our proposed T2V model can generate
  realistic and cinematic-quality videos with a resolution of 1024 times 576,
  outperforming other open-source T2V models in terms of quality. The I2V model
  is designed to produce videos that strictly adhere to the content of the
  provided reference image, preserving its content, structure, and style. This
  model is the first open-source I2V foundation model capable of transforming a
  given image into a video clip while maintaining content preservation
  constraints. We believe that these open-source video generation models will
  contribute significantly to the technological advancements within the
  community.
paper_ai_keywords: diffusion models text-to-video (T2V) image-to-video (I2V) node embedding high-quality video generation resolution realistic videos cinematic-quality reference image content preservation open-source models open-source foundation model