| CARVIEW |
Dream-to-Recon: Monocular 3D Reconstruction with Diffusion-Depth Distillation from Single Images
Philipp Wulff,
Felix Wimbauer,
Dominik Muhle,
Daniel Cremers
ICCV, 2025
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arXiv
We leverage a diffusion model and a depth predictor to generate high-quality scene geometry from a single image. Then, we distill a feed-forward scene reconstruction model, which performs on par with reconstruction methods trained with multi-view supervision. 
Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction
Weirong Chen,
Ganlin Zhang,
Felix Wimbauer,
Rui Wang,
Nikita Araslanov,
Andrea Vedaldi,
Daniel Cremers
ICCV, 2025 (Best Paper Award Candidate, Oral)
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arXiv
A method for consistent dynamic scene reconstruction via motion decoupling, bundle adjustment, and global refinement. 
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
Aleksandar Jevtić*,
Christoph Reich*,
Felix Wimbauer,
Oliver Hahn,
Christian Rupprecht,
Stefan Roth,
Daniel Cremers
ICCV, 2025
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arXiv
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SceneDINO is unsupervised and infers 3D geometry and features from a single image in a feed-forward manner. Distilling and clustering SceneDINO's 3D feature field results in unsupervised semantic scene completion predictions. SceneDINO is trained using multi-view self-supervision. 
AnyCam: Learning to Recover Camera Poses and Intrinsics from Casual Videos
Felix Wimbauer,
Weirong Chen,
Dominik Muhle,
Christian Rupprecht,
Daniel Cremers
CVPR, 2025
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paper
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A method for learning camera poses and intrinsics from dynamic casual videos. 
Cache Me if You Can: Accelerating Diffusion Models through Block Caching
Felix Wimbauer,
Bichen Wu,
Edgar Schoenfeld,
Xiaoliang Dai,
Ji Hou,
Zijian He,
Artsiom Sanakoyeu,
Peizhao Zhang,
Sam Tsai,
Jonas Kohler,
Christian Rupprecht,
Daniel Cremers,
Peter Vajda,
Jialiang Wang
CVPR, 2024
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arXiv
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video
We reuse layer computations from previous timesteps to make image generation with diffusion models more efficient. 
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation
Keonhee Han*,
Dominik Muhle*,
Felix Wimbauer,
Daniel Cremers
CVPR, 2024
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arXiv
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Leveraging multi-view supervision and distillation training to improve volumetric reconstruction from a single image. 
ControlRoom3D: Room Generation using Semantic Proxy Rooms
Jonas Schult,
Sam Tsai,
Lukas Höllein,
Bichen Wu,
Jialiang Wang,
Chih-Yao Ma,
Kunpeng Li,
Xiaofang Wang,
Felix Wimbauer,
Zijian He,
Peizhao Zhang,
Bastian Leibe,
Peter Vajda,
Ji Hou
CVPR, 2024
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arXiv
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video
ControlRoom3D creates diverse and plausible 3D room meshes aligning well with user-defined room layouts and textual descriptions of the room style. 
S4C: Self-Supervised Semantic Scene Completion with Neural Fields
Adrian Hayler*,
Felix Wimbauer*,
Dominik Muhle,
Christian Rupprecht,
Daniel Cremers
3DV, 2024 (Spotlight)
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arXiv
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A self-supervised method for semantic scene completion, that rivals supervised approaches. 
Behind the Scenes: Density Fields for Single View Reconstruction
Felix Wimbauer,
Nan Yang,
Christian Rupprecht,
Daniel Cremers
CVPR, 2023
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arXiv
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video
A self-supervised method for implicit volumetric reconstruction from a single image. 
De-rendering 3D Objects in the Wild
Felix Wimbauer,
Shangzhe Wu,
Christian Rupprecht
CVPR, 2022
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arXiv
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video
A self-supervised method for intrinsic image decomposition. 
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
Felix Wimbauer,
Nan Yang,
Lukas von Stumberg,
Niclas Zeller,
Daniel Cremers
CVPR, 2021
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arXiv
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A state-of-the-art semi-supervised monocular dense reconstruction system, that utilizes a multi-view stereo approach with a filter for moving objects to predict depth maps in dynamic environments. |
