265 Repositories
Python content-loss Libraries
This repository contains the map content ontology used in narrative cartography
Narrative-cartography-ontology This repository contains the map content ontology used in narrative cartography, which is associated with a submission
Dungeons and Dragons randomized content generator
Component based Dungeons and Dragons generator Supports Entity/Monster Generation NPC Generation Weapon Generation Encounter Generation Environment Ge
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model
This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch
This repository contains wordlists for each versions of common web applications and content management systems (CMS). Each version contains a wordlist of all the files directories for this version.
webapp-wordlists This repository contains wordlists for each versions of common web applications and content management systems (CMS). Each version co
Media Replay Engine (MRE) is a framework to build automated video clipping and replay (highlight) generation pipelines for live and video-on-demand content.
Media Replay Engine (MRE) is a framework for building automated video clipping and replay (highlight) generation pipelines using AWS services for live
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss This repository contains the TensorFlow implementation of the paper UnF
[NeurIPS 2021] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples | ⛰️⚠️
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow
Focal Loss for Dense Rotation Object Detection
Convert ResNets weights from GluonCV to Tensorflow Abstract GluonCV released some new resnet pre-training weights and designed some new resnets (such
Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task
multi-task_losses_optimizer Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task 已经实验过了,不会有cuda out of memory情况 ##Par
A database-based CDN node supporting PostgreSQL and MongoDB backends.
A simple to use database-based deployable CDN node for hobbyist developers who wish to have their own CDN!
An official implementation of "Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation" (CVPR 2021) in PyTorch.
BANA This is the implementation of the paper "Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation". For more inf
Unofficial implementation of Proxy Anchor Loss for Deep Metric Learning
Proxy Anchor Loss for Deep Metric Learning Unofficial pytorch, tensorflow and mxnet implementations of Proxy Anchor Loss for Deep Metric Learning. Not
Automated Content Feed Curator
Gathers posts from content feeds, filters, formats, delivers to you.
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
Implementation of the Chamfer Distance as a module for pyTorch
Chamfer Distance for pyTorch This is an implementation of the Chamfer Distance as a module for pyTorch. It is written as a custom C++/CUDA extension.
Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)
Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A
Official implementation for CVPR 2021 paper: Adaptive Class Suppression Loss for Long-Tail Object Detection
Adaptive Class Suppression Loss for Long-Tail Object Detection This repo is the official implementation for CVPR 2021 paper: Adaptive Class Suppressio
Confident Semantic Ranking Loss for Part Parsing
Confident Semantic Ranking Loss for Part Parsing
Unsupervised clustering of high content screen samples
Microscopium Unsupervised clustering and dataset exploration for high content screens. See microscopium in action Public dataset BBBC021 from the Broa
This script runs neural style transfer against the provided content image.
Neural Style Transfer Content Style Output Description: This script runs neural style transfer against the provided content image. The content image m
A Python module for clustering creators of social media content into networks
sm_content_clustering A Python module for clustering creators of social media content into networks. Currently supports identifying potential networks
Python package for visualizing the loss landscape of parameterized quantum algorithms.
orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect
Contrastive Feature Loss for Image Prediction
Contrastive Feature Loss for Image Prediction We provide a PyTorch implementation of our contrastive feature loss presented in: Contrastive Feature Lo
Multi-modal Content Creation Model Training Infrastructure including the FACT model (AI Choreographer) implementation.
AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ [ICCV-2021]. Overview This package contains the model implementation and training
A demo of chinese asr
chinese_asr_demo 一个端到端的中文语音识别模型训练、测试框架 具备数据预处理、模型训练、解码、计算wer等等功能 训练数据 训练数据采用thchs_30,
Editor and Presenter for Manim Generated Content.
Editor and Presenter for Manim Generated Content. Take a look at the Working Example. More information can be found on the documentation. These Browse
MoCoGAN: Decomposing Motion and Content for Video Generation
MoCoGAN: Decomposing Motion and Content for Video Generation This repository contains an implementation and further details of MoCoGAN: Decomposing Mo
Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018
MC-GAN in PyTorch This is the implementation of the Multi-Content GAN for Few-Shot Font Style Transfer. The code was written by Samaneh Azadi. If you
Official implementation for "Image Quality Assessment using Contrastive Learning"
Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi
Deeplab-resnet-101 in Pytorch with Jaccard loss
Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:
Python script for changing the SSH banner content with other content
Banner-changer-py Python script for changing the SSH banner content with other content. The Script will take the content of a specified file range and
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style [NeurIPS 2021] Official code to reproduce the results and data p
Distinguishing Commercial from Editorial Content in News
Distinguishing Commercial from Editorial Content in News In this repository you can find the following: An anonymized version of the data used for my
PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021
Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.
VaporCMS - The greatest content management system that will never exist
The greatest content management system that will never exist Overview WordPress is a huge success but could it be done better? Maybe being mo
Filtering user-generated video content(SberZvukTechDays)Filtering user-generated video content(SberZvukTechDays)
Filtering user-generated video content(SberZvukTechDays) Table of contents General info Team members Technologies Setup Result General info This is a
A package for "Procedural Content Generation via Reinforcement Learning" OpenAI Gym interface.
Readme: Illuminating Diverse Neural Cellular Automata for Level Generation This is the codebase used to generate the results presented in the paper av
Automated GitHub profile content using the USGS API, Plotly and GitHub Actions.
Top 20 Largest Earthquakes in the Past 24 Hours Location Mag Date and Time (UTC) 92 km SW of Sechura, Peru 5.2 11-05-2021 23:19:50 113 km NNE of Lobuj
gwcheck is a tool to check .gnu.warning.* sections in ELF object files and display their content.
gwcheck Description gwcheck is a tool to check .gnu.warning.* sections in ELF object files and display their content. For an introduction to .gnu.warn
A simple tool to test internet stability.
pingtest Description A personal project for testing internet stability, intended for use in Linux and Windows.
Demo content - Automate your automation!
Automate-AAP2 Demo Content - Automate your automation! A fully automated Ansible Automation Platform. Context Installing and configuring Ansible Autom
This tool allows to automatically test for Content Security Policy bypass payloads.
CSPass This tool allows to automatically test for Content Security Policy bypass payloads. Usage [cspass]$ ./cspass.py -h usage: cspass.py [-h] [--no-
Repository for the semantic WMI loss
Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/
Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style disentanglement in image generation and translation" (ICCV 2021)
DiagonalGAN Official Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Trans
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Structural Constraints on Information Content in Human Brain States
Structural Constraints on Information Content in Human Brain States Code accompanying the paper "The information content of brain states is explained
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
An implementation for the loss function proposed in Decoupled Contrastive Loss paper.
Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P
PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric
PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric This repository contains the implementation of MSBG hearing loss m
An extension to detect if the articles content match its title.
Clickbait Detector An extension to detect if the articles content match its title. This was developed in a period of 24-hours in a hackathon called 'H
Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"
Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
Data for "Driving the Herd: Search Engines as Content Influencers" paper
herding_data Data for "Driving the Herd: Search Engines as Content Influencers" paper Dataset description The collection contains 2250 documents, 30 i
Official implementation for the paper: Multi-label Classification with Partial Annotations using Class-aware Selective Loss
Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel
Spatial-Location-Constraint-Prototype-Loss-for-Open-Set-Recognition
Spatial Location Constraint Prototype Loss for Open Set Recognition Official PyTorch implementation of "Spatial Location Constraint Prototype Loss for
The official implementation of Equalization Loss for Long-Tailed Object Recognition (CVPR 2020) based on Detectron2
Equalization Loss for Long-Tailed Object Recognition Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan ⚠️ We re
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)
Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.
CTC Decoding Algorithms Update 2021: installable Python package Python implementation of some common Connectionist Temporal Classification (CTC) decod
Multi-Objective Loss Balancing for Physics-Informed Deep Learning
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Code for ReLoBRaLo. Abstract Physics Informed Neural Networks (PINN) are algorithms
Handling Information Loss of Graph Neural Networks for Session-based Recommendation
LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet)
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet) (
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
Focal Frequency Loss - Official PyTorch Implementation This repository provides the official PyTorch implementation for the following paper: Focal Fre
Code for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss"
PurNet Project for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss" Abstract Image-based salie
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss
CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss This is official implement of "
API to parse tibia.com content into python objects.
Tibia.py An API to parse Tibia.com content into object oriented data. No fetching is done by this module, you must provide the html content. Features:
Disturbing Target Values for Neural Network regularization: attacking the loss layer to prevent overfitting
Disturbing Target Values for Neural Network regularization: attacking the loss layer to prevent overfitting 1. Classification Task PyTorch implementat
LSD (Linux Spotify Downloader) is a command line tool for downloading or rather recording content on Spotify.
LSD (Linux Spotify Downloader) is a command line tool for downloading or rather recording content on Spotify.
Syarat.ID Source Code - Syarat.ID is a content aggregator website
Syarat.ID is a content aggregator website that gathering all informations with the specific keyword: "syarat" from the internet.
Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.
Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.
A script that will warn you, by opening a new browser tab, when there are new content in your favourite websites.
web check A script that will warn you, by opening a new browser tab, when there are new content in your favourite websites. What it does The script wi
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Official implementation of NeurIPS 2021 paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.
Deep Face Recognition in PyTorch
Face Recognition in PyTorch By Alexey Gruzdev and Vladislav Sovrasov Introduction A repository for different experimental Face Recognition models such
Code for visualizing the loss landscape of neural nets
Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer
A CRM department in a local bank works on classify their lost customers with their past datas. So they want predict with these method that average loss balance and passive duration for future.
Rule-Based-Classification-in-a-Banking-Case. A CRM department in a local bank works on classify their lost customers with their past datas. So they wa
NEG loss implemented in pytorch
Pytorch Negative Sampling Loss Negative Sampling Loss implemented in PyTorch. Usage neg_loss = NEG_loss(num_classes, embedding_size) optimizer =
An API that renders HTML/CSS content to PNG using Chromium
html_png An API that renders HTML/CSS content to PNG using Chromium Disclaimer I am not responsible if you happen to make your own instance of this AP
Official pytorch implementation of "Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization" ACMMM 2021 (Oral)
Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization This is an official implementation of "Feature Stylization and Domain-
Implementation of "A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement" by pytorch
This repository is used to suspend the results of our paper "A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement"
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
GeDML is an easy-to-use generalized deep metric learning library
GeDML is an easy-to-use generalized deep metric learning library
This Binance trading bot detects new coins as soon as they are listed on the Binance exchange and automatically places sell and buy orders. It comes with trailing stop loss and other features. If you like this project please consider donating via Brave.
binance-trading-bot-new-coins This Binance trading bot detects new coins as soon as they are listed on the Binance exchange and automatically places s
Exploring Classification Equilibrium in Long-Tailed Object Detection, ICCV2021
Exploring Classification Equilibrium in Long-Tailed Object Detection (LOCE, ICCV 2021) Paper Introduction The conventional detectors tend to make imba
Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators..
ARAPReg Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators.. Installation The cod
TOOD: Task-aligned One-stage Object Detection, ICCV2021 Oral
One-stage object detection is commonly implemented by optimizing two sub-tasks: object classification and localization, using heads with two parallel branches, which might lead to a certain level of spatial misalignment in predictions between the two tasks.
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020)
The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel
The Bot provide Hadith API and fetch content via api.hadith.sutanlab.id
Bot Hadith-API on Telegram The Bot provide Hadith API and fetch content via api.hadith.sutanlab.id Built With Python Asynchronous HTTP protocol client
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation)
Recall Loss for Semantic Segmentation (This repo implements the paper: Recall Loss for Semantic Segmentation) Download Synthia dataset The model uses
A tiny, friendly, strong baseline code for Person-reID (based on pytorch).
Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new
Official PyTorch Implementation of Rank & Sort Loss [ICCV2021]
Rank & Sort Loss for Object Detection and Instance Segmentation The official implementation of Rank & Sort Loss. Our implementation is based on mmdete
The tool helps to find hidden parameters that can be vulnerable or can reveal interesting functionality that other hunters miss.
The tool helps to find hidden parameters that can be vulnerable or can reveal interesting functionality that other hunters miss. Greater accuracy is achieved thanks to the line-by-line comparison of pages, comparison of response code and reflections.
Code for visualizing the loss landscape of neural nets
Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th
WILSON Cloud Respwnder is a Web Interaction Logger Sending Out Notifications with the ability to serve custom content in order to appropriately respond to client-issued requests.
WILSON Cloud Respwnder What is this? WILSON Cloud Respwnder is a Web Interaction Logger Sending Out Notifications (WILSON) with the ability to serve c