activity
20232026
most citedLost & Found: Tracking Changes from Egocentric Observations in 3D Dynamic Scene Graphs

3 citations · 12 across the 19 of their papers we have counts for

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11 papers · 1 filter

cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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,…

cs.RO2025

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…

cs.RO2025

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,…

cs.RO2024★ 3 cited

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…

cs.RO2024★ 2 cited

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…

cs.RO2024★ 1 cited

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…

cs.RO2023★ 3 cited

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…

cs.RO2023

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…

cs.RO2023

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…