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Found 9 papers, 4 papers with code
Leveraging Anchor-based LiDAR 3D Object Detection via Point Assisted Sample Selection
3D object detection based on LiDAR point cloud and prior anchor boxes is a critical technology for autonomous driving environment perception and understanding.
InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers
Planning and prediction are two important modules of autonomous driving and have experienced tremendous advancement recently.
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Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Construction
To enable better integration of satellite maps with existing methods, we propose a hierarchical fusion module, which includes feature-level fusion and BEV-level fusion.
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection
In this paper, we propose a novel and effective Multi-Level Fusion network, named as MLF-DET, for high-performance cross-modal 3D object DETection, which integrates both the feature-level fusion and decision-level fusion to fully utilize the information in the image.
StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition
In this paper, we propose StructVPR, a novel training architecture for VPR, to enhance structural knowledge in RGB global features and thus improve feature stability in a constantly changing environment.
Model-based Decision Making with Imagination for Autonomous Parking
The proposed algorithm consists of three parts: an imaginative model for anticipating results before parking, an improved rapid-exploring random tree (RRT) for planning a feasible trajectory from a given start point to a parking lot, and a path smoothing module for optimizing the efficiency of parking tasks.
Traffic Agent Trajectory Prediction Using Social Convolution and Attention Mechanism
In this paper, we propose a model to predict the trajectories of target agents around an autonomous vehicle.
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network
At present, the performance of deep neural network in general object detection is comparable to or even surpasses that of human beings.
Brain Inspired Cognitive Model with Attention for Self-Driving Cars
Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars.
