467 Open source projects that are alternatives of or similar to Fasterseg

Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19

Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, SAD, PRNet, RESA, LSTR...) based on PyTorch 1.6 with mixed precision training

This repository contains the source code of our work on designing efficient CNNs for computer vision

PSPNet in Chainer

Code for https://arxiv.org/abs/1611.10080

Exploring Cross-Image Pixel Contrast for Semantic Segmentation

Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Understanding Convolution for Semantic Segmentation

Implementation details for EDANet

IJCAI2020 & IJCV 2020 🌇 Unsupervised Scene Adaptation with Memory Regularization in vivo

Official PyTorch implementation of SegFormer

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning

📸 PyTorch implementation of MobileNetV3 for real-time semantic segmentation, with pretrained weights & state-of-the-art performance

Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]

Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

[CVPR 2021] Forecasting the panoptic segmentation of future video frames

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)

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

CGNet: A Light-weight Context Guided Network for Semantic Segmentation [IEEE Transactions on Image Processing 2020]

IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation

ShanghaiTech PLUS Lab Segmentation Toolbox and Benchmark

A PyTorch implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions by Yu and Koltun.

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

TensorFlow-based implementation of "Pyramid Scene Parsing Network".

Implementation of Our ECCV2020-work: Improving Semantic Segmentation via Decoupled Body and Edge Supervision

Pytorch code for semantic segmentation using ERFNet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"

Fully Convolutional HarDNet for Segmentation in Pytorch

TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".

SOTA Semantic Segmentation Models in PyTorch

Depth-wise Asymmetric Bottleneck for Real-time Semantic Segmentation (BMVC2019)

AttaNet for real-time semantic segmentation.

Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

real-time network architecture for mobile devices and semantic segmentation

PyTorch implementation of PNASNet-5 on ImageNet

DeepLabv3, DeepLabv3+ and pretrained weights on VOC & Cityscapes

Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN, RefineNet, DeepLabV3, DeepLabV3+, DenseASPP, BiSegNet)

Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

Segmentation models with pretrained backbones. PyTorch.

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

An extension of Open3D to address 3D Machine Learning tasks

A light-weight, power efficient, and general purpose convolutional neural network

Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

35% faster than ResNet: Harmonic DenseNet, A low memory traffic network

AutoGluon: AutoML for Text, Image, and Tabular Data

[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

Semantic Segmentation Architectures Implemented in PyTorch

A curated list of resources focused on Machine Learning in Geospatial Data Science.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

PyTorch implementation for semantic segmentation (DeepLabV3+, UNet, etc.)

A list of popular deep learning models related to classification, segmentation and detection problems

Single-Stage Semantic Segmentation from Image Labels (CVPR 2020)

Fast and flexible AutoML with learning guarantees.

🚘 Easiest Fully Convolutional Networks

DeepLabv3 built in TensorFlow