6 citations · 11 across the 5 of their papers we have counts for
5 papers
ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling
Radu Beche, Sergiu Nedevschi
The development of aerial holistic scene understanding algorithms is hindered by the scarcity of comprehensive datasets that enable both semantic and geometric reconstruction. Whil…
TanDepth: Leveraging Global DEMs for Metric Monocular Depth Estimation in UAVs
Horatiu Florea, Sergiu Nedevschi
Aerial scene understanding systems face stringent payload restrictions and must often rely on monocular depth estimation for modeling scene geometry, which is an inherently ill-pos…
Forest Inspection Dataset for Aerial Semantic Segmentation and Depth Estimation
Bianca-Cerasela-Zelia Blaga, Sergiu Nedevschi
Humans use UAVs to monitor changes in forest environments since they are lightweight and provide a large variety of surveillance data. However, their information does not present e…
MonoDVPS: A Self-Supervised Monocular Depth Estimation Approach to Depth-aware Video Panoptic Segmentation
Andra Petrovai, Sergiu Nedevschi
Depth-aware video panoptic segmentation tackles the inverse projection problem of restoring panoptic 3D point clouds from video sequences, where the 3D points are augmented with se…
Time-Space Transformers for Video Panoptic Segmentation
Andra Petrovai, Sergiu Nedevschi
We propose a novel solution for the task of video panoptic segmentation, that simultaneously predicts pixel-level semantic and instance segmentation and generates clip-level instan…