7 citations · 7 across the 3 of their papers we have counts for
5 papers
M2H: Multi-Task Learning with Efficient Window-Based Cross-Task Attention for Monocular Spatial Perception
U. V. B. L Udugama, George Vosselman, Francesco Nex
Deploying real-time spatial perception on edge devices requires efficient multi-task models that leverage complementary task information while minimizing computational overhead. Th…
Channel-Aware Distillation Transformer for Depth Estimation on Nano Drones
Ning Zhang, Francesco Nex, George Vosselman +1
Autonomous navigation of drones using computer vision has achieved promising performance. Nano-sized drones based on edge computing platforms are lightweight, flexible, and cheap,…
Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation
Ning Zhang, Francesco Nex, George Vosselman +1
Self-supervised monocular depth estimation that does not require ground truth for training has attracted attention in recent years. It is of high interest to design lightweight but…
Self-supervised monocular depth estimation from oblique UAV videos
Logambal Madhuanand, Francesco Nex, Michael Ying Yang
UAVs have become an essential photogrammetric measurement as they are affordable, easily accessible and versatile. Aerial images captured from UAVs have applications in small and l…
Real-time Semantic Segmentation with Context Aggregation Network
Michael Ying Yang, Saumya Kumaar, Ye Lyu +1
With the increasing demand of autonomous systems, pixelwise semantic segmentation for visual scene understanding needs to be not only accurate but also efficient for potential real…