3 papers
cs.CV2026
IndoorCrowd: A Multi-Scene Dataset for Human Detection, Segmentation, and Tracking with an Automated Annotation Pipeline
Sebastian-Ion Nae, Radu Moldoveanu, Alexandra Stefania Ghita +1
Understanding human behaviour in crowded indoor environments is central to surveillance, smart buildings, and human-robot interaction, yet existing datasets rarely capture real-wor…
cs.CV2026
Learning on the Fly: Replay-Based Continual Object Perception for Indoor Drones
Sebastian-Ion Nae, Mihai-Eugen Barbu, Sebastian Mocanu +1
Autonomous agents such as indoor drones must learn new object classes in real-time while limiting catastrophic forgetting, motivating Class-Incremental Learning (CIL). However, mos…
cs.CV2025
Efficient Self-Supervised Neuro-Analytic Visual Servoing for Real-time Quadrotor Control
Sebastian Mocanu, Sebastian-Ion Nae, Mihai-Eugen Barbu +1
This work introduces a self-supervised neuro-analytical, cost efficient, model for visual-based quadrotor control in which a small 1.7M parameters student ConvNet learns automatica…