3 citations · 29 across the 66 of their papers we have counts for
20 papers · 1 filter
Lost & Found: Tracking Changes from Egocentric Observations in 3D Dynamic Scene Graphs
Tjark Behrens, René Zurbrügg, Marc Pollefeys +2
Recent approaches have successfully focused on the segmentation of static reconstructions, thereby equipping downstream applications with semantic 3D understanding. However, the wo…
HoloSpot: Intuitive Object Manipulation via Mixed Reality Drag-and-Drop
Pablo Soler Garcia, Petar Lukovic, Lucie Reynaud +8
Human-robot interaction through mixed reality (MR) technologies enables novel, intuitive interfaces to control robots in remote operations. Such interfaces facilitate operations in…
ARKit LabelMaker: A New Scale for Indoor 3D Scene Understanding
Guangda Ji, Silvan Weder, Francis Engelmann +2
Neural network performance scales with both model size and data volume, as shown in both language and image processing. This requires scaling-friendly architectures and large datas…
DepthSplat: Connecting Gaussian Splatting and Depth
Haofei Xu, Songyou Peng, Fangjinhua Wang +4
Gaussian splatting and single-view depth estimation are typically studied in isolation. In this paper, we present DepthSplat to connect Gaussian splatting and depth estimation and…
P2P-Bridge: Diffusion Bridges for 3D Point Cloud Denoising
Mathias Vogel, Keisuke Tateno, Marc Pollefeys +3
In this work, we tackle the task of point cloud denoising through a novel framework that adapts Diffusion Schrödinger bridges to points clouds. Unlike previous approaches that pred…
Learning Where to Look: Self-supervised Viewpoint Selection for Active Localization using Geometrical Information
Luca Di Giammarino, Boyang Sun, Giorgio Grisetti +3
Accurate localization in diverse environments is a fundamental challenge in computer vision and robotics. The task involves determining a sensor's precise position and orientation,…
Learning to Make Keypoints Sub-Pixel Accurate
Shinjeong Kim, Marc Pollefeys, Daniel Barath
This work addresses the challenge of sub-pixel accuracy in detecting 2D local features, a cornerstone problem in computer vision. Despite the advancements brought by neural network…
Dynamic 3D Gaussian Fields for Urban Areas
Tobias Fischer, Jonas Kulhanek, Samuel Rota Bulò +3
We present an efficient neural 3D scene representation for novel-view synthesis (NVS) in large-scale, dynamic urban areas. Existing works are not well suited for applications like…
OpenDAS: Open-Vocabulary Domain Adaptation for 2D and 3D Segmentation
Gonca Yilmaz, Songyou Peng, Marc Pollefeys +2
Recently, Vision-Language Models (VLMs) have advanced segmentation techniques by shifting from the traditional segmentation of a closed-set of predefined object classes to open-voc…
NeRFs in Robotics: A Survey
Guangming Wang, Lei Pan, Songyou Peng +7
Detailed and realistic 3D environment representations have been a long-standing goal in the fields of computer vision and robotics. The recent emergence of neural implicit represen…
Spot-Compose: A Framework for Open-Vocabulary Object Retrieval and Drawer Manipulation in Point Clouds
Oliver Lemke, Zuria Bauer, René Zurbrügg +3
In recent years, modern techniques in deep learning and large-scale datasets have led to impressive progress in 3D instance segmentation, grasp pose estimation, and robotics. This…
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views
Francis Engelmann, Fabian Manhardt, Michael Niemeyer +3
Large visual-language models (VLMs), like CLIP, enable open-set image segmentation to segment arbitrary concepts from an image in a zero-shot manner. This goes beyond the tradition…
GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image
Chong Bao, Yinda Zhang, Yuan Li +6
Recently, we have witnessed the explosive growth of various volumetric representations in modeling animatable head avatars. However, due to the diversity of frameworks, there is no…
"Where am I?" Scene Retrieval with Language
Jiaqi Chen, Daniel Barath, Iro Armeni +2
Natural language interfaces to embodied AI are becoming more ubiquitous in our daily lives. This opens up further opportunities for language-based interaction with embodied agents,…
SceneGraphLoc: Cross-Modal Coarse Visual Localization on 3D Scene Graphs
Yang Miao, Francis Engelmann, Olga Vysotska +3
We introduce a novel problem, i.e., the localization of an input image within a multi-modal reference map represented by a database of 3D scene graphs. These graphs comprise multip…
Multi-Level Neural Scene Graphs for Dynamic Urban Environments
Tobias Fischer, Lorenzo Porzi, Samuel Rota Bulò +2
We estimate the radiance field of large-scale dynamic areas from multiple vehicle captures under varying environmental conditions. Previous works in this domain are either restrict…
OpenSUN3D: 1st Workshop Challenge on Open-Vocabulary 3D Scene Understanding
Francis Engelmann, Ayca Takmaz, Jonas Schult +25
This report provides an overview of the challenge hosted at the OpenSUN3D Workshop on Open-Vocabulary 3D Scene Understanding held in conjunction with ICCV 2023. The goal of this wo…
Creating a Digital Twin of Spinal Surgery: A Proof of Concept
Jonas Hein, Frédéric Giraud, Lilian Calvet +8
Surgery digitalization is the process of creating a virtual replica of real-world surgery, also referred to as a surgical digital twin (SDT). It has significant applications in var…
Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion
Zuoyue Li, Zhenqiang Li, Zhaopeng Cui +2
Directly generating scenes from satellite imagery offers exciting possibilities for integration into applications like games and map services. However, challenges arise from signif…
NeRFmentation: NeRF-based Augmentation for Monocular Depth Estimation
Casimir Feldmann, Niall Siegenheim, Nikolas Hars +6
The capabilities of monocular depth estimation (MDE) models are limited by the availability of sufficient and diverse datasets. In the case of MDE models for autonomous driving, th…