There are 19 repositories under spatio-temporal topic.
Fast and Accurate One-Stage Space-Time Video Super-Resolution (accepted in CVPR 2020)
list of papers, code, and other resources
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
Spatio-temporal modeling 论文列表(主要是graph convolution相关)
GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more
ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.
Summary of open source code for deep learning models in the field of traffic prediction
tsl: a PyTorch library for processing spatiotemporal data.
Paper list in traffic prediction field
PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"
A collection of research on spatio-temporal data mining
[ICRA 2021] This repository contains the code for "Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling".
Official Pytorch Implementation for "Space-Time Diffusion Features for Zero-Shot Text-Driven Motion Transfer""
Code for the paper "Spatio-Temporal Neural Networks for Space-Time Series Modeling and Relations Discovery"
Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022
Data Competition Solutions
To keep updates with VRU Grand Challenge, please use https://github.com/NExTplusplus/VidVRD-helper
Mapping spatiotemporal patterns in an online and continuous fashion
3rd Place Solution of KDD Cup 2022-Spatial Dynamic Wind Power Forecasting
[CVPR 2022] Official Pytorch Implementation for "Spatio-temporal Relation Modeling for Few-shot Action Recognition". SOTA Results for Few-shot Action Recognition
A deep generative model to predict aircraft actual trajectories using high dimensional weather data
WATTNet: Learning to Trade FX with Hierarchical Spatio-Temporal Representations of Highly Multivariate Time Series
Paper & Code & Dataset Collection of Spatial-Temporal Data Mining.
A Python package for simple STAC queries
Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022