keras implementation of triplet-loss and triple-center-loss
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Updated
Nov 26, 2019 - Python
keras implementation of triplet-loss and triple-center-loss
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...)
training model using center-loss for face recognition
One-shot face identification using deep learning
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.
The final project of DLCV course (CommE 5052) on NTU
Official companion repository for the paper "A Metric Learning Approach to Misogyny Categorization" at the 5th Workshop on Representation Learning for NLP, ACL 2020
Evaluating the effectiveness of using standalone center loss.
Similarity Learning applied to Speaker Verification and Semantic Textual Similarity
PyTorch Implementation for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors" (ECCVW'20).
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).
Face Recognition Project on Pytorch
Simple Keras implementation of Triplet-Center Loss on the MNIST dataset
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization (ECCV 2020)
This project is intended to solve the task of massive image retrieval.
Deep Attentive Center Loss
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