Popular GitHub Repositories for Ssd300

OpenMMLab Detection Toolbox and Benchmark

Single Shot MultiBox Detector in TensorFlow

SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection

TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet

Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

High quality, fast, modular reference implementation of SSD in PyTorch

MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.

High-performance multiple object tracking based on YOLO, Deep SORT, and KLT ?

A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.

Creating a software for automatic monitoring in online proctoring

People Counting in Real-Time with an IP camera.

convert mmdetection model to tensorrt, support fp16, int8, batch input, dynamic shape etc.

Computer vision based vehicle detection and tracking using Tensorflow Object Detection API and Kalman-filtering

Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs

Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds (CVPR 2022, Oral)

Only implemented through torch: "bi - mamba2" , "vision- mamba2 -torch". support 1d/2d/3d/nd and support export by jit.script/onnx;

CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.

[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

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".