Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
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Updated
Aug 26, 2024 - Python
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Feature Pyramid Networks for Object Detection
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
R2CNN: Rotational Region CNN Based on FPN (Tensorflow)
A Tensorflow implementation of FPN detection framework.
A semantic segmentation toolbox based on PyTorch
This is a tensorflow re-implementation of Feature Pyramid Networks for Object Detection.
Implement of paper 《Attention-guided Context Feature Pyramid Network for Object Detection》
Faster R-CNN / R-FCN đź’ˇ C++ version based on Caffe
A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.
FasterRCNN is implemented in VGG, ResNet and FPN base.
Scalable Instance Segmentation using PyTorch & PyTorch Lightning.
R-DFPN: Rotation Dense Feature Pyramid Networks (Tensorflow)
An easy implementation of FPN (https://arxiv.org/pdf/1612.03144.pdf) in PyTorch.
[BMVC-20] Official PyTorch implementation of PPDet.
QuarkDet lightweight object detection in PyTorch .Real-Time Object Detection on Mobile Devices.
This repository has been moved. The new location is in https://github.com/TexasInstruments/edgeai-tensorlab
Mask R-CNN, FPN, LinkNet, PSPNet and UNet with multiple backbone architectures support readily available
PyTorch implementations of some FPN-based semantic segmentation architectures: vanilla FPN, Panoptic FPN, PANet FPN; with ResNet and EfficientNet backbones.
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