stgcn

There are 0 repository under stgcn topic.

kennymckormick / pyskl
A toolbox for skeleton-based action recognition.
action-recognition deep-learning skeleton-based-action-recognition stgcn posec3d gesture-recognition pytorch
Language:Python 881
Davidham3 / STGCN
implementation of STGCN for traffic prediction in IJCAI2018
ijcai2018 stgcn traffic prediction deep-learning graph-convolutional-network
Language:Python 109
savnani5 / Zero-Shot-Emotion-Recognition-with-AAE
Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders
adverserial-autoencoder gan stgcn vae word-embeddings word2vec zeroshot-learning
Language:Python 5
kaikaic1998 / Unified_Action_Recognition_System
A Unified Action Recognition System that allows the users to fine-tune with only a few videos to suit their unique application.
action-recognition multi-object-tracking pytorch skeleton-based-action-recognition stgcn yolov7 object-detection pose-estimation
Language:Python 3
malswadi / blazepose-skeleton-hmdb-ucf
This is the project repository for the research study Human Action Recognition using BlazePose Skeleton on Spatial Temporal Graph Convolutional Networks presented by Motasem S. Alsawadi and Miguel Rio.
blazepose skeleton stgcn
2
o-ikne / skelmae-shrec24
[SHREC24] Skeleton-based Self-Supervised Learning For Dynamic Hand Gesture Recognition
handgesture-recognition mae self-supervised-learning stgcn shrec24
Language:Python 2
srushtii-m / Jersey-City-CitiBike-Demand-Prediction
Analyzing and predicting the demand for bikes using a Spatio-Temporal Graph Convolutional Network (STGCN) model.
bikeshare-data cnn-pytorch datacleaning eda network-analysis neural-network prediction stgcn
Language:Jupyter Notebook 2
o-ikne / SkelMAE
Skeleton-based Self-Supervised Feature Extraction for Improved Dynamic Hand Gesture Recognition
autoencoder handgesture-recognition handpose mae stgcn fine-tuning self-supervised-learning
1
francescosemeraro / Multi_User_through_Single_User
Repository meant to reproduce the research results of the paper "Towards Multi-User Activity Recognition through Facilitated Training Data and Deep Learning for Human-Robot Collaboration Applications". Please find the AAM at the following link:
activity-recognition deep-learning distributed-strategy gpu lstm multi-user stgcn tensorflow2 transfer-learning vae
Language:Makefile 0

stgcn

kennymckormick / pyskl

Davidham3 / STGCN

savnani5 / Zero-Shot-Emotion-Recognition-with-AAE

kaikaic1998 / Unified_Action_Recognition_System

malswadi / blazepose-skeleton-hmdb-ucf

o-ikne / skelmae-shrec24

srushtii-m / Jersey-City-CitiBike-Demand-Prediction

o-ikne / SkelMAE

francescosemeraro / Multi_User_through_Single_User