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Found 10 papers, 0 papers with code
PPD: A New Valet Parking Pedestrian Fisheye Dataset for Autonomous Driving
In this paper, wepresent the Parking Pedestrian Dataset (PPD), a large-scale fisheye dataset to support research dealing with real-world pedestrians, especially with occlusions and diverse postures.
LineMarkNet: Line Landmark Detection for Valet Parking
We aim for accurate and efficient line landmark detection for valet parking, which is a long-standing yet unsolved problem in autonomous driving.
Graph-Segmenter: Graph Transformer with Boundary-aware Attention for Semantic Segmentation
To address this issue, we propose a Graph-Segmenter, including a Graph Transformer and a Boundary-aware Attention module, which is an effective network for simultaneously modeling the more profound relation between windows in a global view and various pixels inside each window as a local one, and for substantial low-cost boundary adjustment.
ADD: An Automatic Desensitization Fisheye Dataset for Autonomous Driving
The compiled dataset consists of 650K images, including different face and vehicle license plate information captured by the surround-view fisheye camera.
CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion
Channel and spatial attention mechanism has proven to provide an evident performance boost of deep convolution neural networks (CNNs).
Complete Solution for Vehicle Re-ID in Surround-view Camera System
Vehicle re-identification (Re-ID) is a critical component of the autonomous driving perception system, and research in this area has accelerated in recent years.
OCR-RTPS: An OCR-based real-time positioning system for the valet parking
Obtaining the position of ego-vehicle is a crucial prerequisite for automatic control and path planning in the field of autonomous driving.
Surround-view Fisheye BEV-Perception for Valet Parking: Dataset, Baseline and Distortion-insensitive Multi-task Framework
Most existing networks based on public datasets may generalize suboptimal results on these valet parking scenes, also affected by the fisheye distortion.
Detecting Owner-member Relationship with Graph Convolution Network in Fisheye Camera System
The owner-member relationship between wheels and vehicles contributes significantly to the 3D perception of vehicles, especially in embedded environments.
DeepWORD: A GCN-based Approach for Owner-Member Relationship Detection in Autonomous Driving
It's worth noting that the owner-member relationship between wheels and vehicles has an significant contribution to the 3D perception of vehicles, especially in the embedded environment.
