128 citations · 258 across the 27 of their papers we have counts for
43 papers
X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation
Shubhankar Borse, Marvin Klingner, Varun Ravi Kumar +4
Bird's-eye-view (BEV) grid is a common representation for the perception of road components, e.g., drivable area, in autonomous driving. Most existing approaches rely on cameras on…
ViT-BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation
Pramit Dutta, Ganesh Sistu, Senthil Yogamani +2
Generating a detailed near-field perceptual model of the environment is an important and challenging problem in both self-driving vehicles and autonomous mobile robotics. A Bird Ey…
Neuroevolutionary Multi-objective approaches to Trajectory Prediction in Autonomous Vehicles
Fergal Stapleton, Edgar Galván, Ganesh Sistu +1
The incentive for using Evolutionary Algorithms (EAs) for the automated optimization and training of deep neural networks (DNNs), a process referred to as neuroevolution, has gaine…
A Hybrid Sparse-Dense Monocular SLAM System for Autonomous Driving
Louis Gallagher, Varun Ravi Kumar, Senthil Yogamani +1
In this paper, we present a system for incrementally reconstructing a dense 3D model of the geometry of an outdoor environment using a single monocular camera attached to a moving…
Woodscape Fisheye Semantic Segmentation for Autonomous Driving -- CVPR 2021 OmniCV Workshop Challenge
Saravanabalagi Ramachandran, Ganesh Sistu, John McDonald +1
We present the WoodScape fisheye semantic segmentation challenge for autonomous driving which was held as part of the CVPR 2021 Workshop on Omnidirectional Computer Vision (OmniCV)…
BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving
Hazem Rashed, Mariam Essam, Maha Mohamed +2
Detection of moving objects is a very important task in autonomous driving systems. After the perception phase, motion planning is typically performed in Bird's Eye View (BEV) spac…