3 citations · 4 across the 9 of their papers we have counts for
12 papers
Stepper: Stepwise Immersive Scene Generation with Multiview Panoramas
Felix Wimbauer, Fabian Manhardt, Michael Oechsle +4
The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and wor…
Dream-to-Recon: Monocular 3D Reconstruction with Diffusion-Depth Distillation from Single Images
Philipp Wulff, Felix Wimbauer, Dominik Muhle +1
Volumetric scene reconstruction from a single image is crucial for a broad range of applications like autonomous driving and robotics. Recent volumetric reconstruction methods achi…
Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
Aleksandar Jevtić, Christoph Reich, Felix Wimbauer +4
Semantic scene completion (SSC) aims to infer both the 3D geometry and semantics of a scene from single images. In contrast to prior work on SSC that heavily relies on expensive gr…
Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction
Weirong Chen, Ganlin Zhang, Felix Wimbauer +4
Traditional SLAM systems, which rely on bundle adjustment, struggle with highly dynamic scenes commonly found in casual videos. Such videos entangle the motion of dynamic elements,…
AnyCam: Learning to Recover Camera Poses and Intrinsics from Casual Videos
Felix Wimbauer, Weirong Chen, Dominik Muhle +2
Estimating camera motion and intrinsics from casual videos is a core challenge in computer vision. Traditional bundle-adjustment based methods, such as SfM and SLAM, struggle to pe…
Boosting Self-Supervision for Single-View Scene Completion via Knowledge Distillation
Keonhee Han, Dominik Muhle, Felix Wimbauer +1
Inferring scene geometry from images via Structure from Motion is a long-standing and fundamental problem in computer vision. While classical approaches and, more recently, depth m…
Cache Me if You Can: Accelerating Diffusion Models through Block Caching
Felix Wimbauer, Bichen Wu, Edgar Schoenfeld +11
Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the major drawbacks of diffusion…
ControlRoom3D: Room Generation using Semantic Proxy Rooms
Jonas Schult, Sam Tsai, Lukas Höllein +11
Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by genera…
S4C: Self-Supervised Semantic Scene Completion with Neural Fields
Adrian Hayler, Felix Wimbauer, Dominik Muhle +2
3D semantic scene understanding is a fundamental challenge in computer vision. It enables mobile agents to autonomously plan and navigate arbitrary environments. SSC formalizes thi…
Behind the Scenes: Density Fields for Single View Reconstruction
Felix Wimbauer, Nan Yang, Christian Rupprecht +1
Inferring a meaningful geometric scene representation from a single image is a fundamental problem in computer vision. Approaches based on traditional depth map prediction can only…
De-rendering 3D Objects in the Wild
Felix Wimbauer, Shangzhe Wu, Christian Rupprecht
With increasing focus on augmented and virtual reality applications (XR) comes the demand for algorithms that can lift objects from images and videos into representations that are…
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
Felix Wimbauer, Nan Yang, Lukas von Stumberg +2
In this paper, we propose MonoRec, a semi-supervised monocular dense reconstruction architecture that predicts depth maps from a single moving camera in dynamic environments. MonoR…