collaborators

5 papers

cs.CV2026

Action-guided generation of 3D functionality segmentation data

Jaime Corsetti, Francesco Giuliari, Davide Boscaini +6

3D functionality segmentation aims to identify the interactive element in a 3D scene required to perform an action described in free-form language (e.g., the handle to ``Open the s…

cs.CV2026

Generative 6D Pose Estimation via Conditional Flow Matching

Amir Hamza, Davide Boscaini, Weihang Li +2

Existing methods for instance-level 6D pose estimation typically rely on neural networks that either directly regress the pose in or estimate it indirectly via loc…

cs.CV2025

AI-driven visual monitoring of industrial assembly tasks

Mattia Nardon, Stefano Messelodi, Antonio Granata +3

Visual monitoring of industrial assembly tasks is critical for preventing equipment damage due to procedural errors and ensuring worker safety. Although commercial solutions exist,…

cs.CV2025

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…

cs.CV2025

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…