Pytorch implementation of Center Loss
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Updated
Feb 19, 2023 - Python
Pytorch implementation of Center Loss
A PyTorch implementation of center loss on MNIST
One-shot Learning and deep face recognition notebooks and workshop materials
人脸识别算法,结合facenet网络结构和center loss作为损失,基于tensorflow框架,含训练和测试代码,支持从头训练和摄像头测试
An unofficial Gluon FR Toolkit for face recognition. https://gluon-face.readthedocs.io
center loss for face recognition
Open Set Recognition
Deep Face Recognition in PyTorch
Simple Keras implementation of Triplet-Center Loss on the MNIST dataset
Deep Attentive Center Loss
Face Recognition Project on Pytorch
This project is intended to solve the task of massive image retrieval.
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization (ECCV 2020)
Similarity Learning applied to Speaker Verification and Semantic Textual Similarity
This is an implementation of the Center Loss article (2016).
PyTorch Implementation for the paper "C3VQG: Category Consistent Cyclic Visual Question Generation" (ACM MM Asia'20).
keras implementation of A Discriminative Feature Learning Approach for Deep Face Recognition based on MNIST
This repository contains the ipynb for a project on deep learning visual classification of food categories
training model using center-loss for face recognition
PyTorch Implementation for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors" (ECCVW'20).
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