5 papers
Training-Free Hold-Usage Detection in Sport Climbing with Foundation Pose Models
Abu Bakar, Abdullah Aftab, Amir Hamza
Detecting which holds a climber uses, and when, underpins automated scoring, movement analysis, and assistive systems for sport climbing. Existing approaches train task-specific mo…
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…
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…
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…
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…