title: FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View
    Synthesis
summary: Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming,
  from single images is challenging due to a lack of 3D data. To this end, we
  introduce FlexWorld, a novel framework consisting of two key components: (1) a
  strong video-to-video (V2V) diffusion model to generate high-quality novel view
  images from incomplete input rendered from a coarse scene, and (2) a
  progressive expansion process to construct a complete 3D scene. In particular,
  leveraging an advanced pre-trained video model and accurate depth-estimated
  training pairs, our V2V model can generate novel views under large camera pose
  variations. Building upon it, FlexWorld progressively generates new 3D content
  and integrates it into the global scene through geometry-aware scene fusion.
  Extensive experiments demonstrate the effectiveness of FlexWorld in generating
  high-quality novel view videos and flexible-view 3D scenes from single images,
  achieving superior visual quality under multiple popular metrics and datasets
  compared to existing state-of-the-art methods. Qualitatively, we highlight that
  FlexWorld can generate high-fidelity scenes with flexible views like 360{\deg}
  rotations and zooming. Project page: https://ml-gsai.github.io/FlexWorld.
paper_authors._id: 67da8c561a87aaeb4ca06067
paper_authors.name: Luxi Chen
paper_authors.status: admin_assigned
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paper_authors.fullname: luxi chen
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paper_authors.user: lucydetrack
paper_authors._id: 67da8c561a87aaeb4ca06068
paper_authors.name: Zihan Zhou
paper_authors.status: admin_assigned
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paper_authors.fullname: Zhou
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paper_authors.user: ZihanZhou
paper_authors._id: 67da8c561a87aaeb4ca06069
paper_authors.name: Min Zhao
paper_authors._id: 67da8c561a87aaeb4ca0606a
paper_authors.name: Yikai Wang
paper_authors._id: 67da8c561a87aaeb4ca0606b
paper_authors.name: Ge Zhang
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paper_authors.fullname: Ge Zhang
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paper_authors.user: zhangysk
paper_authors._id: 67da8c561a87aaeb4ca0606c
paper_authors.name: Wenhao Huang
paper_authors._id: 67da8c561a87aaeb4ca0606d
paper_authors.name: Hao Sun
paper_authors._id: 67da8c561a87aaeb4ca0606e
paper_authors.name: Ji-Rong Wen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-19T13:39:41.490Z
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paper_authors.fullname: Ji-Rong Wen
paper_authors.type: user
paper_authors.user: jrwen
paper_authors._id: 67da8c561a87aaeb4ca0606f
paper_authors.name: Chongxuan Li
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-19T13:39:35.810Z
paper_authors._id: 64c07b488e2612254361153b
paper_authors.avatarUrl: /avatars/ade0f783cc4c2d3e73f402637f595471.svg
paper_authors.fullname: chongxuan li
paper_authors.type: user
paper_authors.user: zhenxuan00
paper_title: FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View
    Synthesis
paper_summary: Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming,
  from single images is challenging due to a lack of 3D data. To this end, we
  introduce FlexWorld, a novel framework consisting of two key components: (1) a
  strong video-to-video (V2V) diffusion model to generate high-quality novel view
  images from incomplete input rendered from a coarse scene, and (2) a
  progressive expansion process to construct a complete 3D scene. In particular,
  leveraging an advanced pre-trained video model and accurate depth-estimated
  training pairs, our V2V model can generate novel views under large camera pose
  variations. Building upon it, FlexWorld progressively generates new 3D content
  and integrates it into the global scene through geometry-aware scene fusion.
  Extensive experiments demonstrate the effectiveness of FlexWorld in generating
  high-quality novel view videos and flexible-view 3D scenes from single images,
  achieving superior visual quality under multiple popular metrics and datasets
  compared to existing state-of-the-art methods. Qualitatively, we highlight that
  FlexWorld can generate high-fidelity scenes with flexible views like 360{\deg}
  rotations and zooming. Project page: https://ml-gsai.github.io/FlexWorld.
paper_ai_summary: FlexWorld generates high-quality flexible-view 3D scenes from single images using a video-to-video diffusion model and progressive expansion.
paper_ai_keywords: video-to-video diffusion model progressive expansion process pre-trained video model depth-estimated training pairs novel view images camera pose variations geometry-aware scene fusion