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Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)
Code for "Adversarial Camouflage: Hiding Physical World Attacks with Natural Styles" (CVPR 2020)
对抗样本
computer vision learning, include python machine learning action; computer vision based on deep learning ;coursera deeplearning.ai and other cv learning materials collect ...
A novel data-free model stealing method based on GAN
The summer course named Biometric in Depth in NUS
Face is most commonly used biometric to recognize people. Face recognition has received substantial attention from researchers due to human activities found in various applications of security like airport, criminal detection, face tracking, forensic etc. Compared to other biometric traits like palm print, Iris, finger print etc., face biometrics can be non-intrusive. They can be taken even without user’s knowledge and further can be used for security based applications like criminal detection, face tracking, airport security, and forensic surveillance systems. Face recognition involves capturing face image from a video or from a surveillance camera. They are compared with the stored database. Face biometrics involves training known images, classify them with known classes and then they are stored in the database. When a test image is given to the system it is classified and compared with stored database. Face biometrics is a challenging field of research with various limitations imposed for a machine face recognition like variations in head pose, change in illumination, facial expression, aging, occlusion due to accessories etc.,. Various approaches were suggested by researchers in overcoming the limitations stated. 72 Automatic face recognition involves face detection, feature extraction and face recognition. Face recognition algorithms are broadly classified into two classes as image template based and geometric feature based. The template based methods compute correlation between face and one or more model templates to find the face identity. Principal component analysis, linear discriminate analysis, kernel methods etc. are used to construct face templates. The geometric feature based methods are used to analyze explicit local features and their geometric relations (elastic bung graph method). Multi resolution tools such as contour lets, ridge lets were found to be useful for analyzing information content of images and found its application in image processing, pattern recognition, and computer vision. Curvelets transform is used for texture classification and image de-noising. Application of Curvelets transform for feature extraction in image processing is still under research.
Pytorch implementation of face attention network
Crop and Align Face by MTCNN
Face recognition implementation is capable of recognizing faces with occlusion, this includes faces wearing masks.
Face recognition using Tensorflow
Face Analysis Project on PyTorch and MXNet
Tensoflow implementation of InsightFace (ArcFace: Additive Angular Margin Loss for Deep Face Recognition).
Visualizing RNNs using the attention mechanism
Keras implementation of Deep Convolutional Generative Adversarial Networks
《深入理解Linux网络(张彦飞)》; 《内核解密》;
MaskNet is an Occluded face recognition system which capable in recognition masked faces. The project is developed through the research study. the research study can found here. https://www.researchgate.net/project/Face-Mask-Invariant-Face-Recognition-with-Identity-Verification
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
occlusion face recognition
PDSN code for ICCV'2019 paper 《Occlusion Robust Face Recognition based on Mask Learning with Pairwise Differential Siamese Network》
毕业设计基于Opencv的车牌识别系统
Age detection in Tensorflow
基于深度学习的高性能人脸识别引擎Demo
Learning Symmetry Consistent Deep CNNs for Face Completion
整理和注释了facenet的代码,以便更好地理解facenet的代码。源代码地址:https://github.com/davidsandberg/facenet
Awesome resources of yousan.ai(closely related to deep learning).
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.