title: Sora Generates Videos with Stunning Geometrical Consistency
summary: The recently developed Sora model [1] has exhibited remarkable capabilities
  in video generation, sparking intense discussions regarding its ability to
  simulate real-world phenomena. Despite its growing popularity, there is a lack
  of established metrics to evaluate its fidelity to real-world physics
  quantitatively. In this paper, we introduce a new benchmark that assesses the
  quality of the generated videos based on their adherence to real-world physics
  principles. We employ a method that transforms the generated videos into 3D
  models, leveraging the premise that the accuracy of 3D reconstruction is
  heavily contingent on the video quality. From the perspective of 3D
  reconstruction, we use the fidelity of the geometric constraints satisfied by
  the constructed 3D models as a proxy to gauge the extent to which the generated
  videos conform to real-world physics rules. Project page:
  https://sora-geometrical-consistency.github.io/
paper_authors._id: 65dea5fcc1c0850fb97e0f79
paper_authors.name: Xuanyi Li
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-02-28T13:30:43.255Z
paper_authors._id: 65deb47507334f484a61635b
paper_authors.avatarUrl: /avatars/3821a78c535b875d6920519ed20e308f.svg
paper_authors.fullname: XuanyiLi
paper_authors.type: user
paper_authors.user: XuanyiLi
paper_authors._id: 65dea5fcc1c0850fb97e0f7a
paper_authors.name: Daquan Zhou
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-28T12:36:05.889Z
paper_authors._id: 63fe0b160c1bbe8e29d2dd32
paper_authors.avatarUrl: /avatars/bc574036287170a77057893efaa48e2d.svg
paper_authors.fullname: Zhou
paper_authors.type: user
paper_authors.user: DaQuan21
paper_authors._id: 65dea5fcc1c0850fb97e0f7b
paper_authors.name: Chenxu Zhang
paper_authors._id: 65dea5fcc1c0850fb97e0f7c
paper_authors.name: Shaodong Wei
paper_authors._id: 65dea5fcc1c0850fb97e0f7d
paper_authors.name: Qibin Hou
paper_authors._id: 65dea5fcc1c0850fb97e0f7e
paper_authors.name: Ming-Ming Cheng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-02-28T12:37:04.152Z
paper_authors._id: 64e496ae0195913c7fa91c66
paper_authors.avatarUrl: /avatars/23f274f0a3b4ef6ded35205df9bfb564.svg
paper_authors.fullname: chengmingming
paper_authors.type: user
paper_authors.user: mingming8688
paper_title: Sora Generates Videos with Stunning Geometrical Consistency
paper_summary: The recently developed Sora model [1] has exhibited remarkable capabilities
  in video generation, sparking intense discussions regarding its ability to
  simulate real-world phenomena. Despite its growing popularity, there is a lack
  of established metrics to evaluate its fidelity to real-world physics
  quantitatively. In this paper, we introduce a new benchmark that assesses the
  quality of the generated videos based on their adherence to real-world physics
  principles. We employ a method that transforms the generated videos into 3D
  models, leveraging the premise that the accuracy of 3D reconstruction is
  heavily contingent on the video quality. From the perspective of 3D
  reconstruction, we use the fidelity of the geometric constraints satisfied by
  the constructed 3D models as a proxy to gauge the extent to which the generated
  videos conform to real-world physics rules. Project page:
  https://sora-geometrical-consistency.github.io/
paper_ai_summary: A new benchmark evaluates video generation fidelity by assessing the geometric consistency of reconstructed 3D models.
paper_ai_keywords: video generation 3D models geometric constraints real-world physics fidelity