Name: Zhaokun Zhou
Type: User
Company: Peking University
Bio: Ph. D Candidate in Peking University. Interested in Spiking Neural Network and Multimodal Large Language Models.
Location: Shenzhen, China
Zhaokun Zhou's Projects
An open autonomous driving platform
reduce the dimension of images and cluster
A selection of state-of-the-art research materials on trajectory prediction
:sparkles::sparkles:Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
用于从头预训练+SFT一个小参数量的中文LLaMa2的仓库;24G单卡即可运行得到一个具备简单中文问答能力的chat-llama2.
吴恩达老师的机器学习课程个人笔记
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
Deformable DETR: Deformable Transformers for End-to-End Object Detection.
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
hector_slam contains ROS packages related to performing SLAM in unstructed environments like those encountered in the Urban Search and Rescue (USAR) scenarios of the RoboCup Rescue competition.
communicating with Prof.Ding
Dataset, code and model for the CVPR'20 paper "The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction"
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
Frame interpolation
Feature Pyramid Networks in PyTorch
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018
Deep and online learning with spiking neural networks in Python
Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction" CVPR 2020
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints
Spike-Driven Transformer
ICLR 2023, Spikformer: When Spiking Neural Network Meets Transformer
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
PyTorch implementation of Spatial-Temporal Synchronous Graph Convolutional Networks