RobbyYung

RobbyYung's Stars

• ultralytics/ultralytics

  NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

  Language:Python29.1k5.7k

• apachecn/rate-my-supervisor

  Language:JavaScript850123

• hehonghui/awesome-english-ebooks

  经济学人(含音频)、纽约客、卫报、连线、大西洋月刊等英语杂志免费下载,支持epub、mobi、pdf格式, 每周更新

  Language:CSS21.3k1.6k

• programthink/books

  【编程随想】收藏的电子书清单（多个学科，含下载链接）

  18.2k3.3k

• raminhaghjou/Real-Time-Object-Tracking-with-DeepSORT-and-YOLOv8

  Real Time Object Tracking with DeepSORT and YOLOv8 in Google Colab

  Language:Jupyter Notebook41

• computervisioneng/object-tracking-yolov8-deep-sort

  Language:Python9158

• roboflow/supervision

  We write your reusable computer vision tools. 💜

  Language:Python22.7k1.7k

• BonesCat/YoloV5_PyQt5

  Add gui for YoloV5 using PyQt5

  Language:Python14322

• ani8897/Realtime-Action-Recognition

  Contains code for C3D, LCN and TSM for action recognition models.

  Language:Python92

• oulutan/ACAM_Demo

  Real-time Action detection demo for the work Actor Conditioned Attention Maps. This repo includes a complete pipeline for person detection/tracking and analyzing their actions in real-time.

  Language:Python14837

• dakenan1/Realtime-Action-Recognition-Openpose

  A Tensorflow implementation of multi-person action recognition in nine acts

  Language:Jupyter Notebook348

• mbiparva/slowfast-networks-pytorch

  A PyTorch implementation of "SlowFast Networks for Video Recognition"

  Language:Jupyter Notebook204

• dronefreak/human-action-classification

  This repository allows you to classify 40 different human actions. Pose detection, estimation and classification is also performed. Poses are classified into sitting, upright and lying down.

  Language:Python21659

• TianzhongSong/Real-Time-Action-Recognition

  Real-time pose estimation and action recognition

  Language:Python407125

• Queeneren/AD_Library

  主要是AD软件的原理图库和封装库，不断更新ing

  6722

• Whiffe/yolov5-slowfast-deepsort-PytorchVideo

  Language:Python539

• tien02/TrackingwYolov5DeepSORT

  Approaching Pedestrian Tracking problem on surveillance camera with YoloV5 for pedestrian detection and DeepSORT for tracking.

  Language:Python92

• mikel-brostrom/Yolov3_DeepSort_Pytorch

  Real-time multi-person tracker using YOLO v3 and deep sort

  Language:Python16645

• kimyoon-young/centerNet-deep-sort

  realtime multiple people tracking (centerNet based person detector + deep sort algorithm with pytorch)

  Language:Python591148

• theAIGuysCode/yolov4-deepsort

  Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

  Language:Python1.3k750

• Huterox/Real-time-online-multi-target-behavior-detection-project-for-face-recognition

  集成Dlib实现人脸识别模块，以及通过YOLOV5+DeepSort+SlowFast 实现多目标实时在线行为检测。并且开发功能对接接口，可以快速进行二次开发。

  Language:Python239

• Sharpiless/Yolov5-Deepsort

  最新版本yolov5+deepsort目标检测和追踪，能够显示目标类别，支持5.0版本可训练自己数据集

  Language:Python979161

• tomar840/two-stream-fusion-for-action-recognition-in-videos

  Language:Python9028

• amobiny/3D-AlexNet-Tensorflow-Tensorboard

  Implementation of AlexNet for 3D images in Tensorflow

  Language:Python21

• irhum/R2Plus1D-PyTorch

  PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"

  Language:Python36362

• leftthomas/R2Plus1D-C3D

  A PyTorch implementation of R2Plus1D and C3D based on CVPR 2017 paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition" and CVPR 2014 paper "Learning Spatiotemporal Features with 3D Convolutional Networks"

  Language:Python5814

• vra/action-recognition-using-3d-resnet

  Use 3D ResNet to extract features of UCF101 and HMDB51 and then classify them.

  Language:Python3912

• YimianDai/open-aff

  code and trained models for "Attentional Feature Fusion"

  Language:Python72695

• TejInaco/multimodalML

  Language:Python8

• Spareman/Action-recognition-BagOfWords-Early-Late-Fusion

  Video classification using the UCF101 dataset for action recognition. We extract SIFT, MFCC and STIP features from the videos, we encode them using the Bag of Words framework and we implement early and late feature fusion using different combinations of the feature types available.

  Language:Python284