MrRobot-TI

Pinned Repositories

adversarial_examples
对抗样本
Language:Jupyter Notebook00
AdvTrajectoryPrediction
Implementation of CVPR 2022 paper "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles" https://arxiv.org/abs/2201.05057
Language:Python00
c_test
C语言总结
Language:C00
NGSIM-US-101-trajectory-dataset-smoothing
smoothing the NGSIM US-101 trajectory dataset using Savitzky-Golay Filter
Language:Python00
Python-100-Days
Python - 100天从新手到大师
Language:Python00
ResNet18_Cifar10_95.46
Pytorch实现：使用ResNet18网络训练Cifar10数据集，测试集准确率达到95.46%(从0开始，不使用预训练模型)
Language:Python00
Trajectron-plus-plus
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
Language:Jupyter Notebook00

MrRobot-TI's Repositories

MrRobot-TI/AdvTrajectoryPrediction
Implementation of CVPR 2022 paper "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles" https://arxiv.org/abs/2201.05057
MrRobot-TI/Python-100-Days
Python - 100天从新手到大师
MrRobot-TI/adversarial_examples
对抗样本
MrRobot-TI/ResNet18_Cifar10_95.46
Pytorch实现：使用ResNet18网络训练Cifar10数据集，测试集准确率达到95.46%(从0开始，不使用预训练模型)
MrRobot-TI/Trajectron-plus-plus
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
MrRobot-TI/c_test
C语言总结
Language:C
MrRobot-TI/NGSIM-US-101-trajectory-dataset-smoothing
smoothing the NGSIM US-101 trajectory dataset using Savitzky-Golay Filter