mask-rcnn

OpenMMLab Detection Toolbox and Benchmark

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

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

[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come

🌮 Trash Annotations in Context Dataset Toolkit

This is an official implementation for "Contextual Transformer Networks for Visual Recognition".

RectLabel is an offline image annotation tool for object detection and segmentation.

small c++ library to quickly deploy models using onnxruntime

Building detection from the SpaceNet dataset by using Mask RCNN.

[ECCV 2020] Boundary-preserving Mask R-CNN

Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning

Mask R-CNN for object detection and instance segmentation on Pytorch

ICDAR 2019: MaskRCNN on PubLayNet datasets. Paragraph detection, table detection, figure detection,...

Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).

Scalable Instance Segmentation using PyTorch & PyTorch Lightning.

Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.