Applications
Ninja Codes: Neurally Generated Fiducial Markers for Stealthy 6-DoF Tracking
arXiv:2510.18976v2 Announce Type: replace Abstract: In this paper we describe Ninja Codes, neurally generated fiducial markers that can be made to naturally blend into various real-world environments.
arXiv:2510.18976v2 Announce Type: replace Abstract: In this paper we describe Ninja Codes, neurally generated fiducial markers that can be made to naturally blend into various real-world environments. An encoder network converts arbitrary images into Ninja Codes by applying visually modest alterations; the resulting codes, printed and pasted onto surfaces, can provide stealthy 6-DoF location tracking for a wide range of applications including robotics and augmented reality. Ninja Codes can be printed using standard color printers on regular printing paper, and can be detected using any device equipped with a modern RGB camera and capable of running inference. Through experiments, we demonstrate Ninja Codes' ability to provide reliable location tracking under common indoor lighting conditions, while successfully concealing themselves within diverse environmental textures. We expect Ninja Codes to offer particular value in scenarios where the conspicuous appearance of conventional fiducial markers makes them undesirable for aesthetic and other reasons.
Related
- MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation
- R3PM-Net: Real-time, Robust, Real-world Point Matching Network
- MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation
- Scene Change Detection with Vision-Language Representation Learning
- BEM: Training-Free Background Embedding Memory for False-Positive Suppression in Real-Time Fixed-Background Camera
Source: arXiv cs.CV | 2026-04-14