There are 11 repositories under triplet-loss topic.
Siamese and triplet networks with online pair/triplet mining in PyTorch
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
Implementation of triplet loss in TensorFlow
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments
Keras implementation of ‘’Deep Speaker: an End-to-End Neural Speaker Embedding System‘’ (speaker recognition)
A PyTorch implementation of the 'FaceNet' paper for training a facial recognition model with Triplet Loss using the glint360k dataset. A pre-trained model using Triplet Loss is available for download.
Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification
Person re-ID baseline with triplet loss
A PyTorch-based toolkit for natural language processing
Deep Learning - one shot learning for speaker recognition using Filter Banks
A generic triplet data loader for image classification problems,and a triplet loss net demo.
2020/2021 HKUST CSE FYP Masked Facial Recognition, developer: Sam Yuen, Alex Xie, Tony Cheng
Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️
A PyTorch implementation of CGD based on the paper "Combination of Multiple Global Descriptors for Image Retrieval"
Image similarity using Triplet Loss
Complete Code for "Hard-Aware-Deeply-Cascaded-Embedding"
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
Determine whether a given video sequence has been manipulated or synthetically generated
One-Shot Learning with Triplet CNNs in Pytorch
Learning Fine-grained Image Similarity with Deep Ranking is a novel application of neural networks, where the authors use a new multi scale architecture combined with a triplet loss to create a neural network that is able to perform image search. This repository is a simplified implementation of the same
Deepfakes Video classification via CNN, LSTM, C3D and triplets [IWBF'20]
Using SigComp'11 dataset for signature verification
Dogs classification with Deep Metric Learning
Keras implementation of "Deep Learning using Triplet Network" by Hoffer and Ailon. https://arxiv.org/pdf/1412.6622.pdf
This project is intended to solve the task of massive image retrieval.
Who is your doppelgänger and more with Keras face recognition
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization (ECCV 2020)
🍱 R implementation for selected machine learning methods with deep learning frameworks (Keras, Tensorflow)
Simple Keras implementation of Triplet-Center Loss on the MNIST dataset
Face Recognition Project on Pytorch
Official repository for Self-restrained Triplet Loss for Accurate Masked Face Recognition