HuYongting

Scaleda

Scale-able EDA for FPGA, Verilog/Vivado/Quartus and more

CGHMP

code for the paper "Class-guided Human Motion Prediction via Multi-spatial-temporal Supervision"

DCNv2_latest

DCNv2 supports decent pytorch such as torch 1.5+ (now 1.8+)

RANK

AMSTE

RTFM

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

Deep-Learning-Based-Anomaly-Detection

Must-read-papers-and-continuous-tracking-on-Graph-Neural-Network-GNN-progress

Papers on Graph neural network(GNN)

ESL-CN

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

annotated-transformer

An annotated implementation of the Transformer paper.

RecFormer

Code for "Information Recovery-Driven Deep Incomplete Multi-view Clustering Network"

LMVCAT

Code for paper: Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View and Category-Aware Transformers

DIMC

Deep Double Incomplete Multi-view Multi-label Learning with Incomplete Labels and Missing Views

LSIMVC

Localized Sparse Incomplete Multi-view Clustering

DICNet

DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification

nngen

3D-PointCloud

Papers and Datasets about Point Cloud.

flownet2-pytorch

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

DeepMIL

Real-world Anomaly Detection in Surveillance Videos CVPR2018 UCF-Crime dataset

Sound-Anomaly-Detection

A machine learning model that is able to monitor the operations and identify anomalies in audio sounds of the manufacturing equipment.

SoundAnomalyDetectionfromScratch

This is an implemenation of feature extraction in sound from scratch

ToyADMOS-dataset

Dataset and its sample codes for anomaly detection in sound.

awesome-video-anomaly-detection

Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

mmaction2

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

Motorbike-Helmet_detection-using-YOLOV3

This project related to road safety. We have to wear a helmet according to road safety rules when riding a motorcycle. Therefore, these rules are monitored by the police. Also, Due to the invention of high-quality cameras and the development of the state of art in AI, the surveillance system willing to use AI system to detect whether passengers are wearing helmets or not. In this category I have built a model, first, it can be able to detect the motorcycle, then it will find out who is riding the bike. Finally, it will determine whether the person is wearing a helmet or not. To that end, I trained the pre-trained model SSD-MobileNet-V1 to detect motorcycles and humans.