Name: Xing Tang
Type: User
Company: Nanjing University of Science & Technology
Bio: Graduated from Hohai University with a major in Information and Computational Science, currently studying for a master's degree at NJUST
Location: Nanjing,Jiangsu,China
Xing Tang's Projects
2021年的算法实习岗位/校招公司信息表,和常见深度学习基础、计算机视觉知识笔记、算法岗面试题答案,及暑期计算机视觉实习面经和总结。
Official implementation of Adabins: Depth Estimation using adaptive bins
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
An open autonomous driving platform
Erasing Appearance Preservation in Optimization-based Smoothing (ECCV 2020)
👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla
Reading list for research topics in multimodal machine learning
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
An introduction series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.
Computes the Bhattacharyya distance for feature selection in machine learning.
ROS-based code to control a real self-driving car. Final project for "Wolf Pack" team in Udacity's Self-Driving Car Engineer Nanodegree.
Create a path planner that is able to navigate a car safely around a virtual highway
Term 3 Path planning project
Essential Cheat Sheets for deep learning and machine learning researchers
Implement AlphaZero/AlphaGo Zero methods on Chinese chess.
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
YOLO ROS: Real-Time Object Detection for ROS
Repo for the Deep Reinforcement Learning Nanodegree program
PyTorch implementations of deep reinforcement learning algorithms and environments
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Deep Learning Book Chinese Translation
Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
End-to-End Object Detection with Transformers
[TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural network learnt to reproduce the human driver focus of attention (FoA) in a variety of real-world driving scenarios.
Learning where to attend like a human driver
Learning diverse image-to-image translation from unpaired data