Metric Learning
State-of-the-art leaderboards
| Trend | Dataset | Best Method | Paper title | Paper | Code | Compare |
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Greatest papers with code
Time-Contrastive Networks: Self-Supervised Learning from Video
While representations are learned from an unlabeled collection of task-related videos, robot behaviors such as pouring are learned by watching a single 3rd-person demonstration by a human.
metric-learn: Metric Learning Algorithms in Python
metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms.
In Defense of the Triplet Loss for Person Re-Identification
• VisualComputingInstitute/triplet-reid
• 
In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning.
#21 best model for
Person Re-Identification
on Market-1501
Additive Margin Softmax for Face Verification
In this work, we introduce a novel additive angular margin for the Softmax loss, which is intuitively appealing and more interpretable than the existing works.
Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning
CVPR 2019
• loicland/superpoint_graph
• 
We propose a new supervized learning framework for oversegmenting 3D point clouds into superpoints.
NormFace: L2 Hypersphere Embedding for Face Verification
We show that both strategies, and small variants, consistently improve performance by between 0. 2% to 0. 4% on the LFW dataset based on two models.
Matching Networks for One Shot Learning
NeurIPS 2016
• oscarknagg/few-shot
•
Our algorithm improves one-shot accuracy on ImageNet from 87. 6% to 93. 2% and from 88. 0% to 93. 8% on Omniglot compared to competing approaches.
#6 best model for
Few-Shot Image Classification
on OMNIGLOT - 1-Shot Learning
FEW-SHOT IMAGE CLASSIFICATION LANGUAGE MODELLING METRIC LEARNING OMNIGLOT ONE-SHOT LEARNING
Deep Cosine Metric Learning for Person Re-Identification
• nwojke/cosine_metric_learning
•
Metric learning aims to construct an embedding where two extracted features corresponding to the same identity are likely to be closer than features from different identities.
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
• NEU-Gou/awesome-reid-dataset
To ensure a fair comparison, all of the approaches were implemented using a unified code library that includes 11 feature extraction algorithms and 22 metric learning and ranking techniques.
Batch DropBlock Network for Person Re-identification and Beyond
• daizuozhuo/batch-dropblock-network
•
In this paper, we propose the Batch DropBlock (BDB) Network which is a two branch network composed of a conventional ResNet-50 as the global branch and a feature dropping branch.