activity
20242026
collaborators

21 papers

cs.CV2026

TASE: Truncation-Aware Semantic Embeddings for 3D Scene Understanding and Editing

Tim-Felix Faasch, Jochen Kall, Lucas Nunes +2

High-fidelity semantic 3D scene representations are crucial for numerous applications, including robotics, autonomous driving, and simulation. Beyond this, the ability to edit such…

cs.RO2026

DigiForest: Digital Analytics and Robotics for Sustainable Forestry

Marco Camurri, Enrico Tomelleri, Matías Mattamala +18

Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately…

cs.CV2026

Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Colored Point Clouds

Daniel Fusaro, Federico Magistri, Jens Behley +2

Accurate and consistent fruit monitoring over time is a key step toward automated agricultural production systems. However, this task is inherently difficult due to variations in f…

cs.CV2026

Register Any Point: Scaling 3D Point Cloud Registration by Flow Matching

Yue Pan, Tao Sun, Liyuan Zhu +4

Point cloud registration aligns multiple unposed point clouds into a common reference frame and is a core step for 3D reconstruction and robot localization without initial guess. I…

cs.CV2026

Towards Generating Realistic 3D Semantic Training Data for Autonomous Driving

Lucas Nunes, Rodrigo Marcuzzi, Jens Behley +1

Semantic scene understanding is crucial for robotics and computer vision applications. In autonomous driving, 3D semantic segmentation plays an important role for enabling safe nav…

cs.RO2026

SAHA: Supervised Autonomous HArvester for selective forest thinning

Fang Nan, Meher Malladi, Qingqing Li +7

Forestry plays a vital role in our society, creating significant ecological, economic, and recreational value. Efficient forest management involves labor-intensive and complex oper…