G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior
  Integration
We introduce G-CUT3R, a novel feed-forward approach for guided 3D scene
reconstruction that enhances the CUT3R model by integrating prior information.
Unlike existing feed-forward methods that rely solely on input images, our
method leverages auxiliary data, such as depth, camera calibrations, or camera
positions, commonly available in real-world scenarios. We propose a lightweight
modification to CUT3R, incorporating a dedicated encoder for each modality to
extract features, which are fused with RGB image tokens via zero convolution.
This flexible design enables seamless integration of any combination of prior
information during inference. Evaluated across multiple benchmarks, including
3D reconstruction and other multi-view tasks, our approach demonstrates
significant performance improvements, showing its ability to effectively
utilize available priors while maintaining compatibility with varying input
modalities.
68a45c66b65388761d0746d0
Ramil Khafizov
claimed_verified
2025-08-19T11:22:52.622Z
66d07487b86483cf13320564
/avatars/ad59d8edc680336e17a9a4f095a5d0da.svg
Ramil Khafizov
user
smileyenot983
68a45c66b65388761d0746d1
Artem Komarichev
68a45c66b65388761d0746d2
Ruslan Rakhimov
claimed_verified
2025-08-19T11:21:48.836Z
6482ddba57d6e62bf4d8b837
https://cdn-avatars.huggingface.co/v1/production/uploads/6482ddba57d6e62bf4d8b837/XmiNnZ7BB3vgrvEV8nsNI.png
Ruslan Rakhimov
user
rusrakhimov
68a45c66b65388761d0746d3
Peter Wonka
68a45c66b65388761d0746d4
Evgeny Burnaev
G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior
  Integration
We introduce G-CUT3R, a novel feed-forward approach for guided 3D scene
reconstruction that enhances the CUT3R model by integrating prior information.
Unlike existing feed-forward methods that rely solely on input images, our
method leverages auxiliary data, such as depth, camera calibrations, or camera
positions, commonly available in real-world scenarios. We propose a lightweight
modification to CUT3R, incorporating a dedicated encoder for each modality to
extract features, which are fused with RGB image tokens via zero convolution.
This flexible design enables seamless integration of any combination of prior
information during inference. Evaluated across multiple benchmarks, including
3D reconstruction and other multi-view tasks, our approach demonstrates
significant performance improvements, showing its ability to effectively
utilize available priors while maintaining compatibility with varying input
modalities.
G-CUT3R enhances 3D scene reconstruction by integrating auxiliary data through dedicated encoders and zero convolution, improving performance across benchmarks.
CUT3R feed-forward approach guided 3D scene reconstruction auxiliary data depth camera calibrations camera positions dedicated encoder zero convolution RGB image tokens multi-view tasks