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Hi there, I'm Frank Wang

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Working For The Safety of AI!

  • I'm a Ph.D. student in Computer Science, researching AI testing technology.
  • Currently, my main focus is:
    • The safety testing of autonomous driving systems
    • Adversarial example research

Languages and Tools:

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atongwang's Projects

3d_corruptions_ad icon 3d_corruptions_ad

Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving, CVPR 2023

bev-attack icon bev-attack

On the Adversarial Robustness of Camera-based 3D Object Detection

carla-data-export icon carla-data-export

A simple tool for generating training data from the Carla driving simulator

carla-gui icon carla-gui

GUI tool for creating simulation scenarios with Carla simulator

carla-training-data icon carla-training-data

Generating training data from the Carla driving simulator in the KITTI dataset format

carla_apollo_bridge icon carla_apollo_bridge

This project aims to provide a data and control bridge for the communication between the latest version of Apollo and Carla.

msf-adv icon msf-adv

MSF-ADV is a novel physical-world adversarial attack method, which can fool the Multi Sensor Fusion (MSF) based autonomous driving (AD) perception in the victim autonomous vehicle (AV) to fail in detecting a front obstacle and thus crash into it. This work is accepted by IEEE S&P 2021.

nudtpaper icon nudtpaper

A LaTeX template for Master/PhD Thesis of NUDT

off-road-benchmark icon off-road-benchmark

A New Open-Source Off-road Environment for Benchmark Generalization of Autonomous Driving

robobev icon robobev

RoboBEV: Towards Robust Bird's Eye View Perception under Common Corruption and Domain Shift

scenariofuzz icon scenariofuzz

ScenarioFuzz is a framework that focuses on conducting fuzz testing on autonomous driving systems at the scenario level.

sctrans icon sctrans

SCTrans: Constructing a Large Public Scenario Dataset for Simulation Testing of Autonomous Driving Systems

yolov5 icon yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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