531 Open source projects that are alternatives of or similar to Decouplesegnets

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

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

SOTA Semantic Segmentation Models in PyTorch

Official PyTorch implementation of SegFormer

Understanding Convolution for Semantic Segmentation

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

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

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

Pytorch code for semantic segmentation using ERFNet

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

Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

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

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

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

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

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

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

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

[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang

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)

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)

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

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

PSPNet in Chainer

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

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

Implementation details for EDANet

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

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

ShanghaiTech PLUS Lab Segmentation Toolbox and Benchmark

AttaNet for real-time semantic segmentation.

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.)

Exploring Cross-Image Pixel Contrast for Semantic Segmentation

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

Fully convolutional networks for semantic segmentation

Ruby-based framework for acceptance testing

A specification framework for Kotlin

Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.

Code for our ACMMM2020 paper "Context-aware Feature Generation for Zero-shot Semantic Segmentation".

PyTorch-based modular, configuration-driven framework for knowledge distillation. 🏆18 methods including SOTA are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy.

Sandbox for training deep learning networks

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).

An (re-)implementation of DeepLab v2 (ResNet-101) in TensorFlow for semantic image segmentation on the PASCAL VOC 2012 dataset.

[CVPR 2020] Semi-Supervised Semantic Segmentation with Cross-Consistency Training.

Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)

DeepLab-LargeFOV implemented in tensorflow

BDD в 1С

Full Stack Protocol Oriented BDD in Xcode for iOS app with Swift using XCUITest, Cucumberish and FitNesse

Simplest and fastest image and text annotation tool.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

BDD assertion library for Kotlin

Aurora is a project developed in .NET Core, where it aims to show how to create something using an architecture, in layers, simple and approaching, in a simplistic way, some concepts such as DDD.

ICNet and PSPNet-50 in Tensorflow for real-time semantic segmentation

BDD style assertions for node.js -- test framework agnostic

An Official Repo of CVPR '20 "MSeg: A Composite Dataset for Multi-Domain Segmentation"

Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019

Pester is the ubiquitous test and mock framework for PowerShell.