6 citations · 6 across the 18 of their papers we have counts for
7 papers · 1 filter
Applications of Neural Cellular Automata: State of the Art, Challenges and Opportunities
Nick Lemke, Niklas Ihm, John Kalkhof +11
Neural Cellular Automata (NCAs) are a new type of neural network architecture which enable accurate and robust inference at extremely small model sizes. Recently, NCAs have advance…
AgenticCADedit: A Stateful, Tool-Mediated Agentic Approach to Multimodal 3D CAD Editing
Saptarshi Neil Sinha, Mika Silvan Goschke, Paul Julius Kühn +2
Computer-aided design is central to industrial manufacturing, and much of a designer's daily work consists of editing existing models from multimodal requests involving speech, ske…
TinyDETR-Pose: Towards End-to-End Real-Time Single-Stage 6DoF Object Pose Estimation with Lightweight Transformers
Paul Julius Kühn, Duc Anh Nguyen, Saptarshi Neil Sinha +2
Real-time 6DoF object pose estimation on resource-constrained hardware remains challenging, as accurate correspondence-based and refinement pipelines typically rely on non-differen…
ScratchSim: A Procedural Synthetic Data Pipeline for Surface Scratch Detection
Paul Julius Kühn, Saptarshi Neil Sinha, Tiago Kleist +3
While automated defect detection such as the detection of surface scratched is an important aspect in industrial quality control, the scarcity of annotated defect data make this ta…
Beyond Reprojection Error: Camera Calibration with 3D Targets
Dennis Ruppel, Hasan Kutlu, Kai A. Neumann +4
In 3D reconstruction, camera calibration is an essential element for achieving high fidelity and accuracy of the reconstructed geometry. While existing approaches rely upon 2D plan…
SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection
Paul Julius Kühn, Mika Pommeranz, Arjan Kuijper +1
Industrial surface defect inspection suffers from a fundamental data bottleneck: defects are rare, annotations require expert knowledge, and collecting balanced training sets is sl…
Optimizing Multi-Modal Models for Image-Based Shape Retrieval: The Role of Pre-Alignment and Hard Contrastive Learning
Paul Julius Kühn, Cedric Spengler, Michael Weinmann +2
Image-based shape retrieval (IBSR) aims to retrieve 3D models from a database given a query image, hence addressing a classical task in computer vision, computer graphics, and robo…