6 papers
xperception -- Making Robotic Grasping Easier
Matteo Bortolon, Andrea Caraffa, Alice Fasoli +1
The transition toward high-mix low-volume manufacturing demands flexibility in robotic manipulation. However, conventional vision systems remain a bottleneck, requiring extensive d…
Distilling 3D distinctive local descriptors for 6D pose estimation
Amir Hamza, Andrea Caraffa, Davide Boscaini +1
Three-dimensional local descriptors are crucial for encoding geometric surface properties, making them essential for various point cloud understanding tasks. Among these descriptor…
Accurate and efficient zero-shot 6D pose estimation with frozen foundation models
Andrea Caraffa, Davide Boscaini, Fabio Poiesi
Estimating the 6D pose of objects from RGBD data is a fundamental problem in computer vision, with applications in robotics and augmented reality. A key challenge is achieving gene…
CHIP: A multi-sensor dataset for 6D pose estimation of chairs in industrial settings
Mattia Nardon, Mikel Mujika Agirre, Ander González Tomé +7
Accurate 6D pose estimation of complex objects in 3D environments is essential for effective robotic manipulation. Yet, existing benchmarks fall short in evaluating 6D pose estimat…
Wild Berry image dataset collected in Finnish forests and peatlands using drones
Luigi Riz, Sergio Povoli, Andrea Caraffa +13
Berry picking has long-standing traditions in Finland, yet it is challenging and can potentially be dangerous. The integration of drones equipped with advanced imaging techniques r…
FreeZe: Training-free zero-shot 6D pose estimation with geometric and vision foundation models
Andrea Caraffa, Davide Boscaini, Amir Hamza +1
Estimating the 6D pose of objects unseen during training is highly desirable yet challenging. Zero-shot object 6D pose estimation methods address this challenge by leveraging addit…