852 citations · 1.5k across the 82 of their papers we have counts for
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S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving
Maciej K. Wozniak, Hariprasath Govindarajan, Marvin Klingner +3
Recent self-supervised clustering-based pre-training techniques like DINO and Cribo have shown impressive results for downstream detection and segmentation tasks. However, real-wor…
LetsMap: Unsupervised Representation Learning for Semantic BEV Mapping
Nikhil Gosala, Kürsat Petek, B Ravi Kiran +4
Semantic Bird's Eye View (BEV) maps offer a rich representation with strong occlusion reasoning for various decision making tasks in autonomous driving. However, most BEV mapping a…
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…
BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
Jonas Schramm, Niclas Vödisch, Kürsat Petek +4
Semantic scene segmentation from a bird's-eye-view (BEV) perspective plays a crucial role in facilitating planning and decision-making for mobile robots. Although recent vision-onl…
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…