deep learning for image processing including classification and object-detection etc.

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Segmentation models with pretrained backbones. PyTorch.

Pytorch implementation of convolutional neural network visualization techniques

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

A collection of SOTA real-time, multi-object tracking algorithms for object detectors

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

unet for image segmentation

Mask RCNN in TensorFlow

🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOv5, YOLOX, YOLOP, YOLOv6, YOLOR, MODNet, YOLOX, YOLOv7, YOLOv8. MNN, NCNN, TNN, ONNXRuntime.

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

Sandbox for training deep learning networks

A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!