Radar-camera fusion for object detection and semantic segmentation in autonomous driving: A comprehensive review

S Yao, R Guan, X Huang, Z Li, X Sha… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

Dpft: Dual perspective fusion transformer for camera-radar-based object detection

F Fent, A Palffy, H Caesar - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
The perception of autonomous vehicles has to be efficient, robust, and cost-effective.
However, cameras are not robust against severe weather conditions, lidar sensors are …

Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey

K Shi, S He, Z Shi, A Chen, Z **
MP Ronecker, X Diaz, M Karner… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
This paper introduces a novel hybrid architecture that enhances radar-based Dynamic
Occupancy Grid Map** (DOGM) for autonomous vehicles, integrating deep learning for …

Exploiting sparsity in automotive radar object detection networks

M Lippke, M Quach, S Braun, D Köhler, M Ulrich… - arxiv preprint arxiv …, 2023 - arxiv.org
Having precise perception of the environment is crucial for ensuring the secure and reliable
functioning of autonomous driving systems. Radar object detection networks are one …

RCF-TP: Radar-Camera Fusion with Temporal Priors for 3D Object Detection

Y Miron, F Drews, F Faion, D Di Castro, I Klein - IEEE Access, 2024 - ieeexplore.ieee.org
Sensor fusion is an important method for achieving robust perception systems in
autonomous driving, Internet of things, and robotics. Most multi-modal 3D detection models …

A novel chaining-based indirect addressing mode in a vertical vector processor

S Gesper, D Köhler, GB Thieu, J Homann… - … on Embedded Computer …, 2024 - Springer
Efficient processing architectures for irregular data patterns require vector element
addressing with flexible indices. Therefore, state-of-the-art SIMD vector extensions …

DSFEC: Efficient and Deployable Deep Radar Object Detection

G Dandugula, S Boddana, S Mirashi - arxiv preprint arxiv:2412.07411, 2024 - arxiv.org
Deploying radar object detection models on resource-constrained edge devices like the
Raspberry Pi poses significant challenges due to the large size of the model and the limited …