104 citations · 104 across the 4 of their papers we have counts for
4 papers
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…
3D Hierarchical Panoptic Segmentation in Real Orchard Environments Across Different Sensors
Matteo Sodano, Federico Magistri, Elias Marks +6
Crop yield estimation is a relevant problem in agriculture, because an accurate yield estimate can support farmers' decisions on harvesting or precision intervention. Robots can he…
Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
Lucas Nunes, Rodrigo Marcuzzi, Benedikt Mersch +2
Computer vision techniques play a central role in the perception stack of autonomous vehicles. Such methods are employed to perceive the vehicle surroundings given sensor data. 3D…
Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation
Xieyuanli Chen, Benedikt Mersch, Lucas Nunes +4
Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient fo…