Repaint123: Fast and High-quality One Image to 3D Generation with
  Progressive Controllable 2D Repainting
Recent one image to 3D generation methods commonly adopt Score Distillation
Sampling (SDS). Despite the impressive results, there are multiple deficiencies
including multi-view inconsistency, over-saturated and over-smoothed textures,
as well as the slow generation speed. To address these deficiencies, we present
Repaint123 to alleviate multi-view bias as well as texture degradation and
speed up the generation process. The core idea is to combine the powerful image
generation capability of the 2D diffusion model and the texture alignment
ability of the repainting strategy for generating high-quality multi-view
images with consistency. We further propose visibility-aware adaptive
repainting strength for overlap regions to enhance the generated image quality
in the repainting process. The generated high-quality and multi-view consistent
images enable the use of simple Mean Square Error (MSE) loss for fast 3D
content generation. We conduct extensive experiments and show that our method
has a superior ability to generate high-quality 3D content with multi-view
consistency and fine textures in 2 minutes from scratch. Code is at
https://github.com/junwuzhang19/repaint123.
6583b6e33a84a401859e4a92
Junwu Zhang
admin_assigned
2023-12-21T09:11:00.671Z
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Junwu Zhang
user
junwuzhang
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Zhenyu Tang
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2023-12-21T09:11:17.954Z
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Zhenyu Tang
user
royjames
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Yatian Pang
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Xinhua Cheng
admin_assigned
2023-12-21T09:11:43.856Z
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Xinhua Cheng
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cxh0519
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Peng Jin
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2024-10-17T11:31:41.020Z
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Peng Jin
user
Chat-UniVi
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Yida Wei
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Wangbo Yu
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2023-12-21T09:12:46.800Z
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Wangbo Yu
user
Drexubery
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Munan Ning
admin_assigned
2023-12-21T09:12:54.175Z
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/avatars/c6358f81e31f7d31e14899011ce67e09.svg
Munan Ning
user
MasonNing
6583b6e33a84a401859e4a9a
Li Yuan
claimed_verified
2025-04-04T07:12:48.257Z
66135a5e50350afe76beebce
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yl2488
user
yl2488
Repaint123: Fast and High-quality One Image to 3D Generation with
  Progressive Controllable 2D Repainting
Recent one image to 3D generation methods commonly adopt Score Distillation
Sampling (SDS). Despite the impressive results, there are multiple deficiencies
including multi-view inconsistency, over-saturated and over-smoothed textures,
as well as the slow generation speed. To address these deficiencies, we present
Repaint123 to alleviate multi-view bias as well as texture degradation and
speed up the generation process. The core idea is to combine the powerful image
generation capability of the 2D diffusion model and the texture alignment
ability of the repainting strategy for generating high-quality multi-view
images with consistency. We further propose visibility-aware adaptive
repainting strength for overlap regions to enhance the generated image quality
in the repainting process. The generated high-quality and multi-view consistent
images enable the use of simple Mean Square Error (MSE) loss for fast 3D
content generation. We conduct extensive experiments and show that our method
has a superior ability to generate high-quality 3D content with multi-view
consistency and fine textures in 2 minutes from scratch. Code is at
https://github.com/junwuzhang19/repaint123.
A method combining 2D diffusion models and repainting strategies improves 3D image generation quality, consistency, and speed.
Score Distillation Sampling 2D diffusion model repainting strategy visibility-aware adaptive repainting strength multi-view consistent images Mean Square Error (MSE) loss