Python Semantic-similarity Resources

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f

Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m

FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN

FCN-8s implementation in TensorFlow Contents Overview Examples and demo video Dependencies How to use it Download pre-trained VGG-16 Overview This is

semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape

Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the

FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo

Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

##A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation. #USAGE To run the trained classifier on some images: python w

FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the

FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

Fully Convolutional Networks for Semantic Segmentation This is the reference implementation of the models and code for the fully convolutional network

DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC

Pytorch-segmentation-toolbox DOC Pytorch code for semantic segmentation. This is a minimal code to run PSPnet and Deeplabv3 on Cityscape dataset. Shor

Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Fr

DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute

SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te

Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur

project discription An implementation of the Keyword-BERT model mentioned in my paper Keyword-Attentive Deep Semantic Matching (Plz cite this github r

Facial Image Inpainting with Semantic Control In this repo, we provide a model for the controllable facial image inpainting task. This model enables u

Grounding Representation Similarity with Statistical Testing This repo contains code to replicate the results in our paper, which evaluates representa

Multi-View Radar Semantic Segmentation Paper Multi-View Radar Semantic Segmentation, ICCV 2021. Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Flore

Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation (ICCV 2021) [中文|EN] 概述 本工作主要探索一种高效的多传感器（激光雷达和摄像头）融合点云语义分割方法。现有的多传感器融合方法主要将点云投影

Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation This is the code relat

Mining Latent Classes for Few-shot Segmentation Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao. This codebase contains baseline of our paper Mini

DARS Code release for the paper "Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation", ICCV 2021

Multi-Anchor Active Domain Adaptation for Semantic Segmentation Munan Ning*, Donghuan Lu*, Dong Wei†, Cheng Bian, Chenglang Yuan, Shuang Yu, Kai Ma, Y

PSS: Personalized Image Semantic Segmentation Paper PSS: Personalized Image Semantic Segmentation Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang, Ming-Ming

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig

ICCV2021 Papers with Code

CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap

Caboto Caboto, the Kubernetes semantic analysis toolkit. It contains a lightweight Python library for semantic analysis of plain Kubernetes manifests

SegmentationPipeline -- Pytorch A simple pytorch pipeline for semantic segmentation. Requirements : torch=1.9.0 tqdm albumentations=1.0.3 opencv-pyt

Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity Indic TTS Samples can be found at https://peter-yh-wu.github.io/cross-

Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/

K-Net: Towards Unified Image Segmentation Introduction This is an official release of the paper K-Net:Towards Unified Image Segmentation. K-Net will a

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation By Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang SenseTime, Tsinghua Unive

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

TransMaS This repository is the official pytorch implementation of the following paper: NIPS2021 Mixed Supervised Object Detection by TransferringMask

CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized

Contrastive Learning with Non-Semantic Negatives This repository is the official implementation of Robust Contrastive Learning Using Negative Samples

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

IsoTree Fast and multi-threaded implementation of Extended Isolation Forest, Fair-Cut Forest, SCiForest (a.k.a. Split-Criterion iForest), and regular

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

MemSeg: Memory-based semantic segmentation for off-road unstructured natural environments Introduction This repository is a PyTorch implementation of

Auto-Research A no-code utility to generate a detailed well-cited survey with topic clustered sections (draft paper format) and other interesting arti

Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision The PyTorch implementation of DiscoBox: Weakly Supe

Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train

Mesi Mesi is a tool to measure the similarity in a many-to-many fashion of long-form documents like Python source code or technical writing. The outpu

Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

NLP learning Trying to learn NLP to use in my projects! Table of Contents About The Project Built With Getting Started Requirements Run Usage License

BEVNet Datasets Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100. Training BEVNet-S Example: cd experiments bash t

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr

Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Özdemir Cetin & Heinz Koeppl | Pr

Blue Brain Search Source Code DOI Data & Models DOI Documentation Latest Release Python Versions License Build Status Static Typing Code Style Securit

InterFaceGAN - Interpreting the Latent Space of GANs for Semantic Face Editing Figure: High-quality facial attributes editing results with InterFaceGA

Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create

TagLab: an image segmentation tool oriented to marine data analysis TagLab was created to support the activity of annotation and extraction of statist

PyTorch Model Compare A tiny package to compare two neural networks in PyTorch. There are many ways to compare two neural networks, but one robust and

INSPIRED: A Transparent Dialogue Dataset for Interactive Semantic Parsing Existing studies on semantic parsing focus primarily on mapping a natural-la

SPRING This is the repo for SPRING (Symmetric ParsIng aNd Generation), a novel approach to semantic parsing and generation, presented at AAAI 2021. Wi

[ICCV 2021] A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation

PurNet Project for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss" Abstract Image-based salie

Official PyTorch Implementation of Learning Self-Similarity in Space and Time as Generalized Motion for Video Action Recognition, ICCV 2021

MUSCO - Multimodal Descriptions of Social Concepts Automatic Modeling of (Highly Abstract) Social Concepts evoked by Art Images This project aims to i

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

CaLiGraph for Semantic Reasoning Evaluation Challenge This repository contains code and data to use CaLiGraph as a benchmark dataset in the Semantic R

Adversarial text generator Refer to "adversarial_text_generator"[https://github.com/quocnsh/SEPP_generator] project for generating adversarial texts A

Swin Transformer for Semantic Segmentation of satellite images This repo contains the supported code and configuration files to reproduce semantic seg

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision