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Found 6 papers, 3 papers with code
SAM4UDASS: When SAM Meets Unsupervised Domain Adaptive Semantic Segmentation in Intelligent Vehicles
It involves Semantic-Guided Mask Labeling, which assigns semantic labels to unlabeled SAM masks using UDA pseudo-labels.
SUNet: Scale-aware Unified Network for Panoptic Segmentation
Panoptic segmentation combines the advantages of semantic and instance segmentation, which can provide both pixel-level and instance-level environmental perception information for intelligent vehicles.
Threshold-adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation
In stage one, we design a threshold-adaptative unsupervised focal loss to regularize the prediction in the target domain, which has a mild gradient neutralization mechanism and mitigates the problem that hard samples are barely optimized in entropy-based methods.
Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios
As one of the most important tasks in autonomous driving systems, ego-lane detection has been extensively studied and has achieved impressive results in many scenarios.
Monocular Pedestrian Orientation Estimation Based on Deep 2D-3D Feedforward
The 2D and 3D dimensions of pedestrians are determined from the camera captures and further utilized through two feedforward links connected to the orientation estimator.
Joint Calibration of Panoramic Camera and Lidar Based on Supervised Learning
In view of contemporary panoramic camera-laser scanner system, the traditional calibration method is not suitable for panoramic cameras whose imaging model is extremely nonlinear.
