Pytorch Auto DriveSegmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, SAD, PRNet, RESA, LSTR...) based on PyTorch 1.6 with mixed precision training
Stars: ✭ 32 (+10.34%)
Multiclass Semantic Segmentation CamvidTensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.
Stars: ✭ 67 (+131.03%)
Seg MentorTFslim based semantic segmentation models, modular&extensible boutique design
Stars: ✭ 43 (+48.28%)
Deep Residual UnetResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.
Stars: ✭ 97 (+234.48%)
tf-semantic-segmentation-FCN-VGG16Semantic segmentation for classifying road. "Fully Convolutional Networks for Semantic Segmentation (2015)" implemented using TF
Stars: ✭ 30 (+3.45%)
Pytorch Fcn Easiest DemoPyTorch Implementation of Fully Convolutional Networks (a very simple and easy demo).
Stars: ✭ 138 (+375.86%)
Semseg常用的语义分割架构结构综述以及代码复现
Stars: ✭ 624 (+2051.72%)
Pytorch FcnPyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Stars: ✭ 1,351 (+4558.62%)
PiwisePixel-wise segmentation on VOC2012 dataset using pytorch.
Stars: ✭ 365 (+1158.62%)
SegmentationTensorflow implementation : U-net and FCN with global convolution
Stars: ✭ 101 (+248.28%)
Fcn GooglenetGoogLeNet implementation of Fully Convolutional Networks for Semantic Segmentation in TensorFlow
Stars: ✭ 45 (+55.17%)
FcnChainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Stars: ✭ 211 (+627.59%)
StereoNetA customized implementation of the paper "StereoNet: guided hierarchical refinement for real-time edge-aware depth prediction"
Stars: ✭ 107 (+268.97%)
EntityEntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
Stars: ✭ 313 (+979.31%)
panoptic-forecasting[CVPR 2021] Forecasting the panoptic segmentation of future video frames
Stars: ✭ 44 (+51.72%)
squeeze-unetSqueeze-unet Semantic Segmentation for embedded devices
Stars: ✭ 21 (-27.59%)
InstantDLInstantDL: An easy and convenient deep learning pipeline for image segmentation and classification
Stars: ✭ 33 (+13.79%)
kitti deeplabInference script and frozen inference graph with fine tuned weights for semantic segmentation on images from the KITTI dataset.
Stars: ✭ 26 (-10.34%)
recurrent-decoding-cell[AAAI'20] Segmenting Medical MRI via Recurrent Decoding Cell (Spotlight)
Stars: ✭ 14 (-51.72%)
hsn v1HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide Images (ICCV 2019)
Stars: ✭ 65 (+124.14%)
atomaiDeep and Machine Learning for Microscopy
Stars: ✭ 77 (+165.52%)
adversarial-attacksCode for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"
Stars: ✭ 90 (+210.34%)
Swin-TransformerThis is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Stars: ✭ 8,046 (+27644.83%)
SPMLUniversal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning
Stars: ✭ 81 (+179.31%)
night image semantic segmentation[ICIP 2019] : This is the official github repository for the paper "What's There in The Dark" accepted in IEEE International Conference in Image Processing 2019 (ICIP19) , Taipei, Taiwan.
Stars: ✭ 25 (-13.79%)
Fast-SCNN pytorchA PyTorch Implementation of Fast-SCNN: Fast Semantic Segmentation Network(PyTorch >= 1.4)
Stars: ✭ 30 (+3.45%)
Dilation-Pytorch-Semantic-SegmentationA PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.
Stars: ✭ 32 (+10.34%)
super-gradientsEasily train or fine-tune SOTA computer vision models with one open source training library
Stars: ✭ 429 (+1379.31%)
plussegShanghaiTech PLUS Lab Segmentation Toolbox and Benchmark
Stars: ✭ 21 (-27.59%)
wasr networkWaSR Segmentation Network for Unmanned Surface Vehicles v0.5
Stars: ✭ 32 (+10.34%)
SUIMSemantic Segmentation of Underwater Imagery: Dataset and Benchmark. #IROS2020
Stars: ✭ 53 (+82.76%)
Robust-Semantic-SegmentationDynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Stars: ✭ 25 (-13.79%)
satellite-Image-Semantic-Segmentation-Unet-Tensorflow-kerasCollection of different Unet Variant suchas VggUnet, ResUnet, DenseUnet, Unet. AttUnet, MobileNetUnet, NestedUNet, R2AttUNet, R2UNet, SEUnet, scSEUnet, Unet_Xception_ResNetBlock
Stars: ✭ 43 (+48.28%)
mobilenet segmentationBinary semantic segmentation with UNet based on MobileNetV2 encoder
Stars: ✭ 18 (-37.93%)
CVPR2021 PLOPOfficial code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation
Stars: ✭ 102 (+251.72%)
DeepLab-V3Google DeepLab V3 for Image Semantic Segmentation
Stars: ✭ 103 (+255.17%)
BMW-Anonymization-APIThis repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
Stars: ✭ 121 (+317.24%)
flexinferA flexible Python front-end inference SDK based on TensorRT
Stars: ✭ 83 (+186.21%)
deeplabv3plus-kerasdeeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Stars: ✭ 67 (+131.03%)
PixiePixie is a GUI annotation tool which provides the bounding box, polygon, free drawing and semantic segmentation object labelling
Stars: ✭ 52 (+79.31%)
temporal-depth-segmentationSource code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).
Stars: ✭ 20 (-31.03%)
MobileUNETU-NET Semantic Segmentation model for Mobile
Stars: ✭ 39 (+34.48%)
Automated-objects-removal-inpainterAutomated object remover Inpainter is a project that combines Semantic segmentation and EdgeConnect architectures with minor changes in order to remove specified object/s from list of 20 objects from all the input photos
Stars: ✭ 88 (+203.45%)
Segmentation-Series-ChaosSummary and experiment includes basic segmentation, human segmentation, human or portrait matting for both image and video.
Stars: ✭ 75 (+158.62%)