852 citations · 1.5k across the 82 of their papers we have counts for
10 papers · 1 filter
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…
Woodscape Fisheye Object Detection for Autonomous Driving -- CVPR 2022 OmniCV Workshop Challenge
Saravanabalagi Ramachandran, Ganesh Sistu, Varun Ravi Kumar +2
Object detection is a comprehensively studied problem in autonomous driving. However, it has been relatively less explored in the case of fisheye cameras. The strong radial distort…
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes
Sugirtha T, Sridevi M, Khailash Santhakumar +4
Modern object detection architectures are moving towards employing self-supervised learning (SSL) to improve performance detection with related pretext tasks. Pretext tasks for mon…
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving
Sambit Mohapatra, Thomas Mesquida, Mona Hodaei +3
Spiking Neural Networks are a recent and new neural network design approach that promises tremendous improvements in power efficiency, computation efficiency, and processing latenc…
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…
Surround-view Fisheye Camera Perception for Automated Driving: Overview, Survey and Challenges
Varun Ravi Kumar, Ciaran Eising, Christian Witt +1
Surround-view fisheye cameras are commonly used for near-field sensing in automated driving. Four fisheye cameras on four sides of the vehicle are sufficient to cover 360° around t…
UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal
Subhrajyoti Dasgupta, Arindam Das, Senthil Yogamani +4
Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving…
SynWoodScape: Synthetic Surround-view Fisheye Camera Dataset for Autonomous Driving
Ahmed Rida Sekkat, Yohan Dupuis, Varun Ravi Kumar +4
Surround-view cameras are a primary sensor for automated driving, used for near-field perception. It is one of the most commonly used sensors in commercial vehicles primarily used…
Detecting Adversarial Perturbations in Multi-Task Perception
Marvin Klingner, Varun Ravi Kumar, Senthil Yogamani +2
While deep neural networks (DNNs) achieve impressive performance on environment perception tasks, their sensitivity to adversarial perturbations limits their use in practical appli…