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

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

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

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

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

Pytorch implementation of convolutional neural network visualization techniques

BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models

All-in-One Development Tool based on PaddlePaddle（飞桨低代码开发工具）

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

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

unet for image segmentation

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

Segment Anything in High Quality [NeurIPS 2023]

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

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

深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI

Mask RCNN in TensorFlow

A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

Sandbox for training deep learning networks