3 citations · 11 across the 12 of their papers we have counts for
5 papers · 1 filter
Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping
Anas Gouda, Max Schwarz, Christopher Reining +2
Foundation models are a strong trend in deep learning and computer vision. These models serve as a base for applications as they require minor or no further fine-tuning by develope…
Object Pose Estimation Annotation Pipeline for Multi-view Monocular Camera Systems in Industrial Settings
Hazem Youssef, Frederik Polachowski, Jérôme Rutinowski +2
Object localization, and more specifically object pose estimation, in large industrial spaces such as warehouses and production facilities, is essential for material flow operation…
Multi-Channel Time-Series Person and Soft-Biometric Identification
Nilah Ravi Nair, Fernando Moya Rueda, Christopher Reining +1
Multi-channel time-series datasets are popular in the context of human activity recognition (HAR). On-body device (OBD) recordings of human movements are often preferred for HAR ap…
Semi-Automated Computer Vision based Tracking of Multiple Industrial Entities -- A Framework and Dataset Creation Approach
Jérôme Rutinowski, Hazem Youssef, Sven Franke +4
This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, ba…
On the Applicability of Synthetic Data for Re-Identification
Jérôme Rutinowski, Bhargav Vankayalapati, Nils Schwenzfeier +2
This contribution demonstrates the feasibility of applying Generative Adversarial Networks (GANs) on images of EPAL pallet blocks for dataset enhancement in the context of re-ident…