This is an implementation of the Center Loss article (2016).
-
Updated
Jan 21, 2024 - Python
This is an implementation of the Center Loss article (2016).
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization (ECCV 2020)
Based on https://github.com/Arsey/keras-transfer-learning-for-oxford102, but more things are done in the project. Especially for the triplet and center loss.
Official companion repository for the paper "A Metric Learning Approach to Misogyny Categorization" at the 5th Workshop on Representation Learning for NLP, ACL 2020
PyTorch Implementation for the paper "C3VQG: Category Consistent Cyclic Visual Question Generation" (ACM MM Asia'20).
Pytorch implementation of Center Loss
Open Set Recognition
Deep Attentive Center Loss
center loss for face recognition
One-shot face identification using deep learning
PyTorch Implementation for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors" (ECCVW'20).
PyTorch implementation of "Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss"
keras implementation of metric-based methods (center-loss, circle-loss, triplets...)
An unofficial Gluon FR Toolkit for face recognition. https://gluon-face.readthedocs.io
Similarity Learning applied to Speaker Verification and Semantic Textual Similarity
Face Recognition Project on Pytorch
keras implementation of triplet-loss and triple-center-loss
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
Evaluating the effectiveness of using standalone center loss.
Add a description, image, and links to the center-loss topic page so that developers can more easily learn about it.
To associate your repository with the center-loss topic, visit your repo's landing page and select "manage topics."