Name: QiQiQi DONG
Type: User
Company: Delft University of Technology
Bio: Visiting Scholar, UC Berkeley;
Ph.D. researcher, TU Delft;
M.Sc. in Control Science and Engineering, Tsinghua University;
B.Sc. in Telecommunication, BJTU
Twitter: qiyuandream
Location: Delft
Blog: https://www.linkedin.com/in/yongqi-dong-966850105/
QiQiQi DONG's Projects
Data-driven Semi-supervised Machine Learning with Surrogate Measures of Safety for Abnormal Driving Behavior Detection
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
An anonymizer to obfuscate faces and license plates.
Approaching (Almost) Any Machine Learning Problem
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version
awesome-autonomous-driving
Summary of related papers on visual attention. Related code will be released based on Jittor gradually.
Variational Autoencoder for Unsupervised and Disentangled Representation Learning of content and motion features in sequential data (Mandt et al.).
[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
An Ethical Trajectory Planning Algorithm for Autonomous Vehicles
Implementation of Graph Muti-Attention Network with PyTorch
A toolkit for developing and comparing reinforcement learning algorithms.
Hierarchical Neural Networks
A minimalist environment for decision-making in autonomous driving
Codes implementation for "Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning"
Code for the Kaggle Ensembling Guide Article on MLWave
pix2tex: Using a ViT to convert images of equations into LaTeX code.
This is an official repository of End-to-end Lane Shape Prediction with Transformers.
Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
MarkDown 语法
MARL for Autonomous Vehicles
MetaDrive: Composing Diverse Scenarios for Generalizable Reinforcement Learning
PyTorch code for training MM-DistillNet for multimodal knowledge distillation. http://rl.uni-freiburg.de/research/multimodal-distill
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
Hybrid A* Path Planner for the KTH Research Concept Vehicle
code for "Physical-Virtual Collaboration Graph Network for Station-Level Metro Ridership Prediction"