Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.
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Updated
May 29, 2024 - C++
Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.
Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.
Computer vision based vehicle detection and tracking using Tensorflow Object Detection API and Kalman-filtering
[High Performance / MAX 30 FPS] RaspberryPi3(RaspberryPi/Raspbian Stretch) or Ubuntu + Multi Neural Compute Stick(NCS/NCS2) + RealSense D435(or USB Camera or PiCamera) + MobileNet-SSD(MobileNetSSD) + Background Multi-transparent(Simple multi-class segmentation) + FaceDetection + MultiGraph + MultiProcessing + MultiClustering
MobileNetV3-SSD for object detection and implementation in PyTorch
A Light CNN based Method for Hand Detection and Orientation Estimation
Real-time object-detection using SSD on Mobilenet on iOS using CoreML, exported using tf-coreml
BetterNetWork4SSD
This project aims to do real-time object detection through a laptop cam using OpenCV. The idea is to loop over each frame of the video stream, detect objects, and bound each detection in a box.
MobileNets-SSD/SSDLite on VOC/BDD100K Datasets
MobileNet-SSD(MobileNetSSD) + Neural Compute Stick(NCS) Faster than YoloV2 + Explosion speed by RaspberryPi · Multiple moving object detection with high accuracy.
MobilNet-SSD object detection in opencv 3.4.1
How to train an object detection model easy for free
MobileNetV3 SSD的简洁版本
Realtime Object recognition using OpenCV 3.3 dnn module and pretrained MobileNetSSD caffe model
Tensorflow 2 single shot multibox detector (SSD) implementation from scratch with MobileNetV2 and VGG16 backbones
RaspberryPi3(Raspbian Stretch) + MobileNetv2-SSDLite(Tensorflow/MobileNetv2SSDLite) + RealSense D435 + Tensorflow1.11.0 + without Neural Compute Stick(NCS)
Mobilenet SSD based pedestrian detection
Spring 2018 - 10.009 Digital World 1D Project
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