2 citations · 3 across the 11 of their papers we have counts for
15 papers
Foundational feature fusion for conditional flow matching in 6D pose estimation
Amir Hamza, Davide Boscaini, Fabio Poiesi
Conditional flow matching has enabled a step forward in object 6D pose estimation, achieving state-of-the-art performance by progressively denoising and registering object represen…
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…
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…
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,…
An analysis of vision-language models for fabric retrieval
Francesco Giuliari, Asif Khan Pattan, Mohamed Lamine Mekhalfi +1
Effective cross-modal retrieval is essential for applications like information retrieval and recommendation systems, particularly in specialized domains such as manufacturing, wher…
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…