1214 Open source projects that are alternatives of or similar to MaskedFaceRepresentation

A new large-scale noise-controlled face recognition dataset.

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection

Python & Matlab code for local feature descriptor evaluation with the HPatches dataset.

BIRL: Benchmark on Image Registration methods with Landmark validations

A MNIST-like fashion product database. Benchmark 👇

ConMask model described in paper Open-world Knowledge Graph Completion.

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

MaskedFace-Net is a dataset of human faces with a correctly and incorrectly worn mask based on the dataset Flickr-Faces-HQ (FFHQ).

The PatchCamelyon (PCam) deep learning classification benchmark.

Dataset and code for the paper "First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations", CVPR 2018.

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A repository of pretty cool datasets that I collected for network science and machine learning research.

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Convert face dataset to masked dataset

FaceRank - Rank Face by CNN Model based on TensorFlow (add keras version). FaceRank-人脸打分基于 TensorFlow (新增 Keras 版本) 的 CNN 模型（QQ群：167122861）。技术支持：http://tensorflow123.com

A curated list of repositories for my book Machine Learning Solutions.

[CVPR 2020] A Large-Scale Dataset for Real-World Face Forgery Detection

Evaluation of the CNN design choices performance on ImageNet-2012.

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A benchmark dataset for data-driven weather forecasting

A simple gravitational N-body simulation in less than 100 lines of C code, with CUDA optimizations.

Face Recognition in real-world images [ICASSP 2017]

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DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020

A list of tools, papers and code related to Deepfake Detection.

No description or website provided.

🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

[DEPRECATED] Imitate an API for downloading data from Facebook Data For Good

CSS in JS Benchmarks for React Native

Face detection & recognition AR app using the mlmodel to recognize company employees.

IGUANA is a benchmark execution framework for querying HTTP endpoints and CLI Applications such as Triple Stores. Contact: [email protected]

Miscellaneous benchmarks for JSON serialization on JVM/Android

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

Trace memory allocations and collect stats

VGG-Face CNN descriptor in PyTorch.

An Innovative Salient Object Detection Using Center-Dark Channel Prior

A GPU-accelerated real-time face recognition system based on classical machine learning algorithms

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This framework provides logging, benchmarking and monitoring.

simple example face recognition with deep metric learning to dlib

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Benchmark to compare async web server + interpreter + web client implementations across various languages

MVP Benchmark for Multi-View Partial Point Cloud Completion and Registration

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A micro-benchmark framework to use with cargo bench

No description or website provided.

Benchmark your application on CI

ArcSoft Face SDK Demo

This repo is meant for backend API for face comparision and computer vision. It is built on python flask framework

A benchmark program for dgraph.

Reference github repository for the paper "Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data". We propose a procedure to generate realistic DP data synthetically. Our synthesis approach mimics the optical image formation found on DP sensors and can be applied to virtual scenes rendered with standard computer software. Lev…

CPU Ultimate Latency Test.

The Audit Test Automation Package gives you the ability to get an overview about the compliance status of several systems. You can easily create HTML-reports and have a transparent overview over compliance and non-compliance of explicit setttings and configurations in comparison to industry standards and hardening guides.