There are 52 repositories under segmentation topic.
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.
SOTA real-time, multi-object tracking 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
Mask RCNN in TensorFlow
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
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
🛠 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.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
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
Collection of papers, datasets, code and other resources for object tracking and detection using deep learning
Pytorch framework for doing deep learning on point clouds.
Awesome GAN for Medical Imaging
Unsupervised Word Segmentation for Neural Machine Translation and Text Generation
A procedural Blender pipeline for photorealistic training image generation
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
Papers and Datasets about Point Cloud.
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
Convolutional Neural Network for 3D meshes in PyTorch
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
《深度学习与计算机视觉》配套代码