Dawei Zhao

Orcid: 0000-0002-4583-1268

Affiliations:
  • Unmanned Systems Technology Research Center, Defense Innovation Institute, Beijing, China
  • National University of Defense Technology, College of Intelligence Science and Technology, Changsha, Hunan, China


According to our database1, Dawei Zhao authored at least 28 papers between 2014 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
TPKD: Teacher-Pruned Knowledge Distillation for Point Cloud-Based 3D Object Detection.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2025

2024
Occupancy-MAE: Self-Supervised Pre-Training Large-Scale LiDAR Point Clouds With Masked Occupancy Autoencoders.
IEEE Trans. Intell. Veh., July, 2024

Deep Reinforcement Learning: A Survey.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Multi-Camera Unified Pre-Training via 3D Scene Reconstruction.
IEEE Robotics Autom. Lett., 2024

Autonomous Driving in Unstructured Environments: How Far Have We Come?
CoRR, 2024

Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond.
CoRR, 2024

A Two-Stage Active Domain Adaptation Framework for Vehicle Re-Identification.
Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

Pre-pruned Distillation for Point Cloud-based 3D Object Detection.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

DriveWorld: 4D Pre-Trained Scene Understanding via World Models for Autonomous Driving.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Traversability analysis for autonomous driving in complex environment: A LiDAR-based terrain modeling approach.
J. Field Robotics, October, 2023

TOM-Odometry: A Generalized Localization Framework Based on Topological Map and Odometry.
IEEE Trans. Aerosp. Electron. Syst., June, 2023

Adversarial and Random Transformations for Robust Domain Adaptation and Generalization.
Sensors, 2023

UniWorld: Autonomous Driving Pre-training via World Models.
CoRR, 2023

Occ-BEV: Multi-Camera Unified Pre-training via 3D Scene Reconstruction.
CoRR, 2023

Self-Supervised Embodied Learning for Semantic Segmentation.
Proceedings of the IEEE International Conference on Development and Learning, 2023

2022
Voxel-MAE: Masked Autoencoders for Pre-training Large-scale Point Clouds.
CoRR, 2022

Trajectory Prediction for Autonomous Driving with Topometric Map.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

ORFD: A Dataset and Benchmark for Off-Road Freespace Detection.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
Attentional Graph Neural Network for Parking-Slot Detection.
IEEE Robotics Autom. Lett., 2021

2020
Drosophila-inspired 3D moving object detection based on point clouds.
Inf. Sci., 2020

A Guide-line and Key-point based A-star Path Planning Algorithm For Autonomous Land Vehicles.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Self-Supervised Domain Adaptation with Consistency Training.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Augmenting cascaded correlation filters with spatial-temporal saliency for visual tracking.
Inf. Sci., 2019

2018
Multi-Object Tracking with Correlation Filter for Autonomous Vehicle.
Sensors, 2018

Automatic Extrinsic Calibration of Monocular Camera and LIDAR in Natural Scenes.
Proceedings of the IEEE International Conference on Information and Automation, 2018

2016
Multi-cue road boundary detection using stereo vision.
Proceedings of the IEEE International Conference on Vehicular Electronics and Safety, 2016

2014
Efficient Vehicle Localization Based on Road-Boundary Maps.
Proceedings of the PRICAI 2014: Trends in Artificial Intelligence, 2014

Night-Time Road Boundary Detection with Infrared Channel Features Classifier.
Proceedings of the 14th IEEE International Conference on Computer and Information Technology, 2014


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