FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View
  Synthesis
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.
67da8c561a87aaeb4ca06067
Luxi Chen
admin_assigned
2025-03-19T13:39:20.898Z
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luxi chen
user
lucydetrack
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Zihan Zhou
admin_assigned
2025-03-19T13:39:28.536Z
64586db4bb7bdc9655afb5ce
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Zhou
user
ZihanZhou
67da8c561a87aaeb4ca06069
Min Zhao
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Yikai Wang
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Ge Zhang
admin_assigned
2025-03-19T13:40:15.137Z
638efcf4c67af472d316d424
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Ge Zhang
user
zhangysk
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Wenhao Huang
67da8c561a87aaeb4ca0606d
Hao Sun
67da8c561a87aaeb4ca0606e
Ji-Rong Wen
admin_assigned
2025-03-19T13:39:41.490Z
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Ji-Rong Wen
user
jrwen
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Chongxuan Li
admin_assigned
2025-03-19T13:39:35.810Z
64c07b488e2612254361153b
/avatars/ade0f783cc4c2d3e73f402637f595471.svg
chongxuan li
user
zhenxuan00
FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View
  Synthesis
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.
FlexWorld generates high-quality flexible-view 3D scenes from single images using a video-to-video diffusion model and progressive expansion.
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