A toolbox for skeleton-based action recognition.

implementation of STGCN for traffic prediction in IJCAI2018

[PLOS ONE] Official implementation of the paper "SignFormer-GCN : Continuous Sign Language Translation Using Spatio-Temporal Graph Convolutional Networks"

Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders

[SHREC24] Skeleton-based Self-Supervised Learning For Dynamic Hand Gesture Recognition

A Unified Action Recognition System that allows the users to fine-tune with only a few videos to suit their unique application.

AG-MAE: Anatomically Guided Spatio-Temporal Masked Auto-Encoder for Online Hand Gesture Recognition

Vietnamese Sign Language Recognition

CSDC 연구실 낙상 감지 모듈

An AI-driven Adaptive Traffic Signal Control System (ATSCS) that replaces static timers with dynamic green-light phases. Utilizes YOLOv8 for real-time vehicle density estimation and multi-class classification, achieving 96.4% mAP. Optimized for low-latency inference (>30 FPS) on edge devices to reduce urban congestion and commuter wait times.

Human Activity Recognition using Deep Learning for classifying human activities from wearable sensor data through preprocessing, feature extraction, and neural network-based classification.

Data-driven spatiotemporal water quality prediction using ANN and STGCN with multi-source environmental data

ТГУ | Магистратура "Компьютерное зрение и нейронные сети" | Распознавание действий по скелетным данным для онлайн-кинотеатра KION. Работа выполнена в рамках хакатона по курсу.