← Core Methods
Machine Learning › Core Methods ›

Metric Learning

2800 directly classified papers

Papers per year

Papers

Point Cloud Oversegmentation With Graph-Structured Deep Metric Learning CVPR 2019
SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking CVPR 2019
3D Instance Segmentation via Multi-Task Metric Learning ICCV 2019
PANet: Few-Shot Image Semantic Segmentation With Prototype Alignment ICCV 2019
Vehicle Re-Identification With Viewpoint-Aware Metric Learning ICCV 2019
MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-Identification ICCV 2019
Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking CVPR 2019
Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings ICCV 2019
Deep Metric Learning With Tuplet Margin Loss ICCV 2019
Local Aggregation for Unsupervised Learning of Visual Embeddings ICCV 2019
Video Face Clustering With Unknown Number of Clusters ICCV 2019
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning ICCV 2019
Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training ICCV 2019
Ranked List Loss for Deep Metric Learning CVPR 2019
DynTypo: Example-Based Dynamic Text Effects Transfer CVPR 2019
A Similarity Measurement Method Based on Graph Kernel for Disconnected Graphs IJCAI 2019
Refining Word Representations by Manifold Learning IJCAI 2019
End-to-End Multi-Perspective Matching for Entity Resolution IJCAI 2019
Heterogeneous Graph Matching Networks for Unknown Malware Detection IJCAI 2019
Extensible Cross-Modal Hashing IJCAI 2019
Triplet Enhanced AutoEncoder: Model-free Discriminative Network Embedding IJCAI 2019
Supervised Short-Length Hashing IJCAI 2019
Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances IJCAI 2019
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders NIPS 2019
Representation Learning-Assisted Click-Through Rate Prediction IJCAI 2019