There are 12 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.
Person re-ID baseline with triplet loss
Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification
Deep Learning - one shot learning for speaker recognition using Filter Banks
A PyTorch-based toolkit for natural language processing
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"
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.
Image similarity using Triplet Loss
Complete Code for "Hard-Aware-Deeply-Cascaded-Embedding"
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]
Dogs classification with Deep Metric Learning
Using SigComp'11 dataset for signature verification
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.
CARLA: A self-supervised contrastive learning model for time series anomaly detection. Enhances anomaly detection by learning robust representations of time series data.
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