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Found 19 papers, 5 papers with code
Communication-Efficient MARL for Platoon Stability and Energy-efficiency Co-optimization in Cooperative Adaptive Cruise Control of CAVs
Cooperative adaptive cruise control (CACC) has been recognized as a fundamental function of autonomous driving, in which platoon stability and energy efficiency are outstanding challenges that are difficult to accommodate in real-world operations.
EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy Network
On Occ3D-nuScenes benchmark, EFFOcc has only 18. 4M parameters, and achieves 50. 46 in terms of mean IoU (mIoU), to our knowledge, it is the occnet with minimal parameters compared with related occnets.
PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving
For foreground instance grouping, we propose a novel 3D instance mask decoder that can efficiently extract individual objects.
DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model
Constructing high-definition (HD) maps is a crucial requirement for enabling autonomous driving.
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving
A map, as crucial information for downstream applications of an autonomous driving system, is usually represented in lanelines or centerlines.
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
In this paper, we present XuanCe, a comprehensive and unified deep reinforcement learning (DRL) library designed to be compatible with PyTorch, TensorFlow, and MindSpore.
Dynamically Conservative Self-Driving Planner for Long-Tail Cases
In this way, the DCP is designed to automatically adjust to be more conservative in low-confidence "long-tail" cases while keeping efficient otherwise.
Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving
By constraining the uncertainty, the DRL model's performance is always greater than that of a baseline policy.
Poses as Queries: Image-to-LiDAR Map Localization with Transformers
High-precision vehicle localization with commercial setups is a crucial technique for high-level autonomous driving tasks.
Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review
Given the lack of current surveys for this rapidly expanding field, we present a hierarchically-structured review of grid-centric perception for autonomous vehicles.
StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation
Predicting the future occupancy states of the surrounding environment is a vital task for autonomous driving.
Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detection
A novel method that realizes the feature-level fusion under the bird's-eye view (BEV) for a better feature representation is proposed.
Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles
To this end, this work proposes a trajectory planner to consider the prediction model uncertainty arising from insufficient data for safer performance.
SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking
Our novel sparse feature sampling module only utilizes local 2D region of interest (RoI) features calculated by the projection of 3D query boxes for further box refinement, leading to a fully-convolutional and deployment-friendly pipeline.
Ranked #8 on
Robust Camera Only 3D Object Detection
on nuScenes-C
BE-STI: Spatial-Temporal Integrated Network for Class-Agnostic Motion Prediction With Bidirectional Enhancement
In this paper, we propose a novel Spatial-Temporal Integrated network with Bidirectional Enhancement, BE-STI, to improve the temporal motion prediction performance by spatial semantic features, which points out an efficient way to combine semantic segmentation and motion prediction.
PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving
The accelerating development of autonomous driving technology has placed greater demands on obtaining large amounts of high-quality data.
Locality Constrained Analysis Dictionary Learning via K-SVD Algorithm
With the learned analysis dictionary, test samples can be transformed into a sparse subspace for classification efficiently.
Enhancement of Superconductivity Linked with Linear-in-Temperature/Field Resistivity in Ion-Gated FeSe Films
Iron selenide (FeSe) - the structurally simplest iron-based superconductor, has attracted tremendous interest in the past years.
Superconductivity
Three-dimensional charge density wave and robust zero-bias conductance peak inside the superconducting vortex core of a kagome superconductor CsV$_3$Sb$_5$
The transition-metal-based kagome metals provide a versatile platform for correlated topological phases hosting various electronic instabilities.
Superconductivity Strongly Correlated Electrons
