142 citations · 146 across the 6 of their papers we have counts for
10 papers
FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving
Ganesh Sistu, Senthil Yogamani
Object detection is a mature problem in autonomous driving with pedestrian detection being one of the first deployed algorithms. It has been comprehensively studied in the literatu…
DaF-BEVSeg: Distortion-aware Fisheye Camera based Bird's Eye View Segmentation with Occlusion Reasoning
Senthil Yogamani, David Unger, Venkatraman Narayanan +1
Semantic segmentation is an effective way to perform scene understanding. Recently, segmentation in 3D Bird's Eye View (BEV) space has become popular as its directly used by drive…
Impact of Video Compression Artifacts on Fisheye Camera Visual Perception Tasks
Madhumitha Sakthi, Louis Kerofsky, Varun Ravi Kumar +1
Autonomous driving systems require extensive data collection schemes to cover the diverse scenarios needed for building a robust and safe system. The data volumes are in the order…
Neural Rendering based Urban Scene Reconstruction for Autonomous Driving
Shihao Shen, Louis Kerofsky, Varun Ravi Kumar +1
Dense 3D reconstruction has many applications in automated driving including automated annotation validation, multimodal data augmentation, providing ground truth annotations for s…
Multi-camera Bird's Eye View Perception for Autonomous Driving
David Unger, Nikhil Gosala, Varun Ravi Kumar +3
Most automated driving systems comprise a diverse sensor set, including several cameras, Radars, and LiDARs, ensuring a complete 360°coverage in near and far regions. Unlike Radar…
X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation
Shubhankar Borse, Senthil Yogamani, Marvin Klingner +4
Bird's-eye-view (BEV) grid is a typical representation of the perception of road components, e.g., drivable area, in autonomous driving. Most existing approaches rely on cameras on…