DeepMove
Human Mobility Model
A PyTorch-based implementation of a predictive model for human mobility patterns using attention mechanisms and recurrent neural networks.
Codes for WWW'18 Paper-DeepMove: Predicting Human Mobility with Attentional Recurrent Network
144 stars
3 watching
56 forks
Language: Python
last commit: over 4 years ago
Linked from 1 awesome list
attentionmobility-trajectorypredictionwww
protontypes/open-sustainable-technologyRelated projects:
| Repository | Description | Stars |
|---|---|---|
 pxiangwu/motionnet | Develops accurate perception and motion prediction models for autonomous vehicles based on 2D maps | 169 |
 mrgemy95/visual-interaction-networks-pytorch | An implementation of Deepmind's Visual Interaction Networks using PyTorch to predict future events in physical scenes. | 166 |
 l0sg/relational-rnn-pytorch | An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch for word language modeling | 244 |
 doctorteeth/diffmem | Differentiable memory schemes for neural networks | 220 |
 mhjabreel/stf-rnn | Recurrent neural network model for predicting people's next location based on spatial and temporal features | 28 |
 horseee/deepcache | A novel paradigm to accelerate diffusion models by reusing and updating high-level features in a cheap way | 796 |
 xxradon/igcv3-pytorch | Reimplements MobileNet-V2 and IGCV3 using PyTorch for efficient deep learning. | 19 |
 javeywang/pyramid-attention-networks-pytorch | An implementation of a deep learning model using PyTorch for semantic segmentation tasks. | 235 |
 rozumden/defmo | A deep learning framework for deblurring and recovering the shape of fast-moving objects from blurred images | 170 |
 wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 849 |
 isht7/pytorch-deeplab-resnet | A deep learning model implementation of the DeepLab ResNet architecture for image segmentation tasks. | 602 |
 tinghuiz/sfmlearner | An unsupervised learning framework for depth and ego-motion estimation from monocular videos | 1,967 |
 benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 363 |
 radimspetlik/si-ddpm-fmo | A Python-based framework for training and evaluating deep learning models for single-image deblurring, shape, and trajectory recovery of fast-moving objects. | 5 |
 hongwenzhang/pymaf | Reconstructs human 3D models from monocular images using a feedback loop to improve pose and shape estimation | 596 |