1 citations · 1 across the 3 of their papers we have counts for
4 papers
ProGuT: Label-Efficient Panoptic Segmentation for Forest Scenes
Pankaj Deoli, Karsten Berns
Panoptic segmentation in forest environments is bottlenecked not by semantic quality but by instance separation; existing unsupervised panoptic approaches produce usable stuff maps…
Granularity-Aware Transfer for Tree Instance Segmentation in Synthetic and Real Forests
Pankaj Deoli, Atef Tej, Anmol Ashri +2
We address the challenge of synthetic-to-real transfer in forestry perception where real data have only coarse Tree labels while synthetic data provide fine-grained trunk/crown ann…
Preliminary analysis of RGB-NIR Image Registration techniques for off-road forestry environments
Pankaj Deoli, Karthik Ranganath, Karsten Berns
RGB-NIR image registration plays an important role in sensor-fusion, image enhancement and off-road autonomy. In this work, we evaluate both classical and Deep Learning (DL) based…
Evaluating the Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric analysis
Pankaj Deoli, Rohit Kumar, Axel Vierling +1
This study investigates the vulnerability of semantic segmentation models to adversarial input perturbations, in the domain of off-road autonomous driving. Despite good performance…