3 citations · 12 across the 19 of their papers we have counts for
21 papers
Map-Det3D: Metric Feed-Forward 3D Reconstruction Prior for Multi-view 3D Object Detection from Streaming Inputs
Yung-Hsu Yang, Luigi Piccinelli, Samuel Rota Bulò +7
Metric 3D object detection is a core capability for embodied agents, yet most reliable systems lean on depth sensors, trading away cost, power, and integration simplicity. This mot…
DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving
Yung-Hsu Yang, Luigi Piccinelli, Siyuan Li +8
Safe autonomous navigation requires a holistic understanding of dynamic environments, necessitating the simultaneous estimation of metric depth, semantic segmentation, and instance…
LIME: Learning Intent-aware Camera Motion from Egocentric Video
Boyang Sun, Jiajie Li, Yung-Hsu Yang +6
Autonomous robots often need to move their camera before they can act: to inspect an object, reveal an occluded region, or obtain a view that responds to a user's intent. While vis…
Hoi! - A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation
Tim Engelbracht, René Zurbrügg, Matteo Wohlrapp +5
We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during real human interaction. The dataset…
ActLoc: Learning to Localize on the Move via Active Viewpoint Selection
Jiajie Li, Boyang Sun, Luca Di Giammarino +2
Reliable localization is critical for robot navigation, yet most existing systems implicitly assume that all viewing directions at a location are equally informative. In practice,…
3D-MOOD: Lifting 2D to 3D for Monocular Open-Set Object Detection
Yung-Hsu Yang, Luigi Piccinelli, Mattia Segu +6
Monocular 3D object detection is valuable for various applications such as robotics and AR/VR. Existing methods are confined to closed-set settings, where the training and testing…
Spot-On: A Mixed Reality Interface for Multi-Robot Cooperation
Tim Engelbracht, Petar Lukovic, Tjark Behrens +5
Recent progress in mixed reality (MR) and robotics is enabling increasingly sophisticated forms of human-robot collaboration. Building on these developments, we introduce a novel M…
Loop Closure from Two Views: Revisiting PGO for Scalable Trajectory Estimation through Monocular Priors
Tian Yi Lim, Boyang Sun, Marc Pollefeys +1
(Visual) Simultaneous Localization and Mapping (SLAM) remains a fundamental challenge in enabling autonomous systems to navigate and understand large-scale environments. Traditiona…
FrontierNet: Learning Visual Cues to Explore
Boyang Sun, Hanzhi Chen, Stefan Leutenegger +3
Exploration of unknown environments is crucial for autonomous robots; it allows them to actively reason and decide on what new data to acquire for different tasks, such as mapping,…
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…
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,…
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…
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…
"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,…
LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories
Silvan Weder, Hermann Blum, Francis Engelmann +1
Semantic annotations are indispensable to train or evaluate perception models, yet very costly to acquire. This work introduces a fully automated 2D/3D labeling framework that, wit…
SNI-SLAM: Semantic Neural Implicit SLAM
Siting Zhu, Guangming Wang, Hermann Blum +4
We propose SNI-SLAM, a semantic SLAM system utilizing neural implicit representation, that simultaneously performs accurate semantic mapping, high-quality surface reconstruction, a…
A 3D Mixed Reality Interface for Human-Robot Teaming
Jiaqi Chen, Boyang Sun, Marc Pollefeys +1
This paper presents a mixed-reality human-robot teaming system. It allows human operators to see in real-time where robots are located, even if they are not in line of sight. The o…
Active Visual Localization for Multi-Agent Collaboration: A Data-Driven Approach
Matthew Hanlon, Boyang Sun, Marc Pollefeys +1
Rather than having each newly deployed robot create its own map of its surroundings, the growing availability of SLAM-enabled devices provides the option of simply localizing in a…